{"about":{"non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","site":"https://codewithpapers.app","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page","syntology":{"site":"https://syntology.ai","developers":"https://syntology.ai/developers","mcp":{"server":"https://syntology.ai/mcp","transport":"streamable-http","server_card":"https://syntology.ai/.well-known/mcp/server-card.json","auth":{"type":"trial token, no account","trial_token":"https://syntology.ai/api/oauth/trial/token","method":"POST","docs":"https://syntology.ai/developers"}},"have":"https://syntology.ai/api/graph/have?x=<method, arXiv id or title> (free, answers coverage only)","paper_base":"https://syntology.ai/paper/","atlas_base":"https://app.syntology.ai/?focus="},"machine_readable":[{"url":"https://codewithpapers.app/llms.txt","what":"the machine catalog: every machine-readable file, counted"},{"url":"https://codewithpapers.app/index/manifest.json","what":"paper-to-code index by arXiv id, with Syntology's counts"},{"url":"https://codewithpapers.app/search/manifest.json","what":"site search index (titles, authors) and its files"},{"url":"https://codewithpapers.app/download","what":"bulk files: Syntology's layer, described there"},{"url":"https://codewithpapers.app/build_manifest.json","what":"the build record: inputs, counts, exclusions, probes"}]},"url":"/task/large-language-model/papers/ran/7","list_of":"/task/large-language-model","task":"Large Language Model","archive":{"snapshot":"2025-07-28"},"key_notes":{"n_ran_checked":"legacy name, kept unchanged so existing readers do not break: it counts the samples that ran with no instrument failure (honoured, violated, and ran with no contract checked); it does not mean a contract was checked, and the pages print it as 'K with no instrument failure', not 'K checked'","n_constructed":"a sub-count of the samples that ran, never subtracted from them and never a failure: an executed sample whose run returned an instance of its own class (fixture_out_type equals the entry name): the run built an object and did not compute a result (Syntology's RAN record, counts.constructed)"},"syntology_read_at":"2026-09-28T10:30:06+00:00","order":"ran","order_definition":"only papers where Syntology ran at least one harvested sample; date (newest first), ties by arXiv id","caption":"We ran code from the paper's repository; we did not run it on this task or check it against the task's benchmarks.","absence":"A paper missing from this list is not a recorded non-run: it may have no arXiv id, no harvested code, or only samples that have not run yet.","page":7,"pages_in_order":9,"rows_per_page":100,"rows":[601,700],"of":801,"counts":{"archive_papers_tagged":6097,"with_a_code_link":2250,"where_syntology_ran_a_sample":801,"not_listed_spam_title":0,"listed":6097,"listed_where_code_ran":801,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":683,"every_run_a_failure_of_syntologys_instrument":118,"listed_with_a_run_with_no_instrument_failure":683,"listed_every_run_a_failure_of_syntologys_instrument":118,"filter":{"states":["a run with no instrument failure","any run, instrument failures included"],"default":"a run with no instrument failure","note":"on the 'only where code ran' pages the default hides, in the browser, the rows where every run was a failure of Syntology's instrument; the second state shows them again. Rows are hidden, never re-ordered; these twins list every row"}},"definition":"distinct papers the archive tags; 'where Syntology ran a sample' counts papers with at least one harvested sample that ran, which is not a correctness claim"},"first_page":"/task/large-language-model/papers/ran/1","prev":"/task/large-language-model/papers/ran/6","next":"/task/large-language-model/papers/ran/8","papers":[{"url":"/paper/u-llava-unifying-multi-modal-tasks-via-large","slug":"u-llava-unifying-multi-modal-tasks-via-large","title":"u-LLaVA: Unifying Multi-Modal Tasks via Large Language Model","date":"2023-11-09","arxiv_id":"2311.05348","repositories_listed":1,"syntology":{"n":7,"n_ran":6,"n_constructed":0,"n_ran_checked":5,"n_instrument":1,"n_unverified":1,"n_honours":1,"n_violates":0,"n_no_contract":4,"n_pointer_only":2,"phrase":"6 ran (of which 0 constructed an object rather than computing a result; 5 with no instrument failure: 1 honoured, 0 violated, 4 with no contract checked; 1 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/u-llava-unifying-multi-modal-tasks-via-large#ran","syntology_url":"https://syntology.ai/paper/2311.05348","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2311.05348"}},"official":{"repos":["OPPOMKLab/u-LLaVA"],"state":"official (archive's flag): 6 ran","n_ran":6,"n_constructed":0,"n_ran_no_instrument_failure":5,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/unified-low-resource-sequence-labeling-by","slug":"unified-low-resource-sequence-labeling-by","title":"Unified Low-Resource Sequence Labeling by Sample-Aware Dynamic Sparse Finetuning","date":"2023-11-07","arxiv_id":"2311.03748","repositories_listed":1,"syntology":{"n":14,"n_ran":11,"n_constructed":0,"n_ran_checked":11,"n_instrument":0,"n_unverified":3,"n_honours":0,"n_violates":0,"n_no_contract":11,"n_pointer_only":3,"phrase":"11 ran (of which 0 constructed an object rather than computing a result; 11 with no instrument failure: 0 honoured, 0 violated, 11 with no contract checked; 0 where Syntology's instrument failed) · 3 unverified","sample_list":"/paper/unified-low-resource-sequence-labeling-by#ran","syntology_url":"https://syntology.ai/paper/2311.03748","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2311.03748"}},"official":{"repos":["psunlpgroup/fish-dip"],"state":"official (archive's flag): 11 ran","n_ran":11,"n_constructed":0,"n_ran_no_instrument_failure":11,"n_unverified":3,"ran_from_kinds":["official"]}}},{"url":"/paper/large-language-model-based-long-tail-query","slug":"large-language-model-based-long-tail-query","title":"Large Language Model based Long-tail Query Rewriting in Taobao Search","date":"2023-11-07","arxiv_id":"2311.03758","repositories_listed":1,"syntology":{"n":4,"n_ran":1,"n_constructed":0,"n_ran_checked":1,"n_instrument":0,"n_unverified":3,"n_honours":0,"n_violates":0,"n_no_contract":1,"n_pointer_only":0,"phrase":"1 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 0 violated, 1 with no contract checked; 0 where Syntology's instrument failed) · 3 unverified","sample_list":"/paper/large-language-model-based-long-tail-query#ran","syntology_url":"https://syntology.ai/paper/2311.03758","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2311.03758"}},"official":null}},{"url":"/paper/aspects-of-human-memory-and-large-language","slug":"aspects-of-human-memory-and-large-language","title":"Aspects of human memory and Large Language Models","date":"2023-11-07","arxiv_id":"2311.03839","repositories_listed":1,"syntology":{"n":3,"n_ran":1,"n_constructed":0,"n_ran_checked":1,"n_instrument":0,"n_unverified":2,"n_honours":0,"n_violates":0,"n_no_contract":1,"n_pointer_only":0,"phrase":"1 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 0 violated, 1 with no contract checked; 0 where Syntology's instrument failed) · 2 unverified","sample_list":"/paper/aspects-of-human-memory-and-large-language#ran","syntology_url":"https://syntology.ai/paper/2311.03839","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2311.03839"}},"official":{"repos":["rmldj/memory-llm-paper"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":2,"ran_from_kinds":["official"]}}},{"url":"/paper/locating-cross-task-sequence-continuation","slug":"locating-cross-task-sequence-continuation","title":"Towards Interpretable Sequence Continuation: Analyzing Shared Circuits in Large Language Models","date":"2023-11-07","arxiv_id":"2311.04131","repositories_listed":1,"syntology":{"n":4,"n_ran":4,"n_constructed":0,"n_ran_checked":4,"n_instrument":0,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":4,"n_pointer_only":0,"phrase":"4 ran (of which 0 constructed an object rather than computing a result; 4 with no instrument failure: 0 honoured, 0 violated, 4 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/locating-cross-task-sequence-continuation#ran","syntology_url":"https://syntology.ai/paper/2311.04131","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2311.04131"}},"official":{"repos":["apartresearch/seqcont_circuits"],"state":"official (archive's flag): 4 ran","n_ran":4,"n_constructed":0,"n_ran_no_instrument_failure":4,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/mplug-owl2-revolutionizing-multi-modal-large","slug":"mplug-owl2-revolutionizing-multi-modal-large","title":"mPLUG-Owl2: Revolutionizing Multi-modal Large Language Model with Modality Collaboration","date":"2023-11-07","arxiv_id":"2311.04257","repositories_listed":2,"syntology":{"n":3,"n_ran":1,"n_constructed":0,"n_ran_checked":0,"n_instrument":1,"n_unverified":2,"n_honours":0,"n_violates":0,"n_no_contract":0,"n_pointer_only":3,"phrase":"1 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 1 where Syntology's instrument failed) · 2 unverified","sample_list":"/paper/mplug-owl2-revolutionizing-multi-modal-large#ran","syntology_url":"https://syntology.ai/paper/2311.04257","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2311.04257"}},"official":{"repos":["x-plug/mplug-owl"],"state":"official: no sample here; runs from other or unrecorded repositories","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["unlocated"]}}},{"url":"/paper/deepinception-hypnotize-large-language-model","slug":"deepinception-hypnotize-large-language-model","title":"DeepInception: Hypnotize Large Language Model to Be Jailbreaker","date":"2023-11-06","arxiv_id":"2311.03191","repositories_listed":1,"syntology":{"n":3,"n_ran":3,"n_constructed":0,"n_ran_checked":3,"n_instrument":0,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":3,"n_pointer_only":0,"phrase":"3 ran (of which 0 constructed an object rather than computing a result; 3 with no instrument failure: 0 honoured, 0 violated, 3 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/deepinception-hypnotize-large-language-model#ran","syntology_url":"https://syntology.ai/paper/2311.03191","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2311.03191"}},"official":{"repos":["tmlr-group/deepinception"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":3,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/effective-human-ai-teams-via-learned-natural-1","slug":"effective-human-ai-teams-via-learned-natural-1","title":"Effective Human-AI Teams via Learned Natural Language Rules and Onboarding","date":"2023-11-02","arxiv_id":"2311.01007","repositories_listed":1,"syntology":{"n":12,"n_ran":8,"n_constructed":0,"n_ran_checked":8,"n_instrument":0,"n_unverified":4,"n_honours":0,"n_violates":0,"n_no_contract":8,"n_pointer_only":12,"phrase":"8 ran (of which 0 constructed an object rather than computing a result; 8 with no instrument failure: 0 honoured, 0 violated, 8 with no contract checked; 0 where Syntology's instrument failed) · 4 unverified","sample_list":"/paper/effective-human-ai-teams-via-learned-natural-1#ran","syntology_url":"https://syntology.ai/paper/2311.01007","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2311.01007"}},"official":{"repos":["clinicalml/onboarding_human_ai"],"state":"official (archive's flag): 8 ran","n_ran":8,"n_constructed":0,"n_ran_no_instrument_failure":8,"n_unverified":4,"ran_from_kinds":["official"]}}},{"url":"/paper/collaborative-large-language-model-for","slug":"collaborative-large-language-model-for","title":"Collaborative Large Language Model for Recommender Systems","date":"2023-11-02","arxiv_id":"2311.01343","repositories_listed":1,"syntology":{"n":2,"n_ran":2,"n_constructed":0,"n_ran_checked":2,"n_instrument":0,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":2,"n_pointer_only":0,"phrase":"2 ran (of which 0 constructed an object rather than computing a result; 2 with no instrument failure: 0 honoured, 0 violated, 2 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/collaborative-large-language-model-for#ran","syntology_url":"https://syntology.ai/paper/2311.01343","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2311.01343"}},"official":{"repos":["yaochenzhu/llm4rec"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":0,"n_ran_no_instrument_failure":2,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/plug-and-play-policy-planner-for-large","slug":"plug-and-play-policy-planner-for-large","title":"Plug-and-Play Policy Planner for Large Language Model Powered Dialogue Agents","date":"2023-11-01","arxiv_id":"2311.00262","repositories_listed":1,"syntology":{"n":9,"n_ran":8,"n_constructed":0,"n_ran_checked":7,"n_instrument":1,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":7,"n_pointer_only":9,"phrase":"8 ran (of which 0 constructed an object rather than computing a result; 7 with no instrument failure: 0 honoured, 0 violated, 7 with no contract checked; 1 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/plug-and-play-policy-planner-for-large#ran","syntology_url":"https://syntology.ai/paper/2311.00262","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2311.00262"}},"official":{"repos":["dengyang17/ppdpp"],"state":"official (archive's flag): 7 ran","n_ran":7,"n_constructed":0,"n_ran_no_instrument_failure":7,"n_unverified":1,"ran_from_kinds":["community","official"]}}},{"url":"/paper/large-language-model-can-interpret-latent","slug":"large-language-model-can-interpret-latent","title":"Large Language Model Can Interpret Latent Space of Sequential Recommender","date":"2023-10-31","arxiv_id":"2310.20487","repositories_listed":2,"syntology":{"n":7,"n_ran":5,"n_constructed":0,"n_ran_checked":3,"n_instrument":2,"n_unverified":2,"n_honours":2,"n_violates":0,"n_no_contract":1,"n_pointer_only":7,"phrase":"5 ran (of which 0 constructed an object rather than computing a result; 3 with no instrument failure: 2 honoured, 0 violated, 1 with no contract checked; 2 where Syntology's instrument failed) · 2 unverified","sample_list":"/paper/large-language-model-can-interpret-latent#ran","syntology_url":"https://syntology.ai/paper/2310.20487","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2310.20487"}},"official":{"repos":["yangzhengyi98/recinterpreter"],"state":"community repositories only","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["listed"]}}},{"url":"/paper/competeai-understanding-the-competition","slug":"competeai-understanding-the-competition","title":"CompeteAI: Understanding the Competition Dynamics in Large Language Model-based Agents","date":"2023-10-26","arxiv_id":"2310.17512","repositories_listed":1,"syntology":{"n":5,"n_ran":1,"n_constructed":0,"n_ran_checked":1,"n_instrument":0,"n_unverified":4,"n_honours":0,"n_violates":0,"n_no_contract":1,"n_pointer_only":0,"phrase":"1 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 0 violated, 1 with no contract checked; 0 where Syntology's instrument failed) · 4 unverified","sample_list":"/paper/competeai-understanding-the-competition#ran","syntology_url":"https://syntology.ai/paper/2310.17512","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2310.17512"}},"official":{"repos":["microsoft/competeai"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":4,"ran_from_kinds":["official"]}}},{"url":"/paper/crash-clustering-removing-and-sharing-enhance","slug":"crash-clustering-removing-and-sharing-enhance","title":"CRaSh: Clustering, Removing, and Sharing Enhance Fine-tuning without Full Large Language Model","date":"2023-10-24","arxiv_id":"2310.15477","repositories_listed":1,"syntology":{"n":4,"n_ran":3,"n_constructed":1,"n_ran_checked":1,"n_instrument":2,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":1,"n_pointer_only":4,"phrase":"3 ran (of which 1 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 0 violated, 1 with no contract checked; 2 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/crash-clustering-removing-and-sharing-enhance#ran","syntology_url":"https://syntology.ai/paper/2310.15477","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2310.15477"}},"official":{"repos":["tsinghuac3i/crash"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":1,"n_ran_no_instrument_failure":1,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/lorashear-efficient-large-language-model","slug":"lorashear-efficient-large-language-model","title":"LoRAShear: Efficient Large Language Model Structured Pruning and Knowledge Recovery","date":"2023-10-24","arxiv_id":"2310.18356","repositories_listed":2,"syntology":{"n":3,"n_ran":1,"n_constructed":0,"n_ran_checked":1,"n_instrument":0,"n_unverified":2,"n_honours":0,"n_violates":0,"n_no_contract":1,"n_pointer_only":0,"phrase":"1 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 0 violated, 1 with no contract checked; 0 where Syntology's instrument failed) · 2 unverified","sample_list":"/paper/lorashear-efficient-large-language-model#ran","syntology_url":"https://syntology.ai/paper/2310.18356","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2310.18356"}},"official":null}},{"url":"/paper/llm-in-the-loop-leveraging-large-language","slug":"llm-in-the-loop-leveraging-large-language","title":"LLM-in-the-loop: Leveraging Large Language Model for Thematic Analysis","date":"2023-10-23","arxiv_id":"2310.15100","repositories_listed":1,"syntology":{"n":3,"n_ran":3,"n_constructed":0,"n_ran_checked":3,"n_instrument":0,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":3,"n_pointer_only":3,"phrase":"3 ran (of which 0 constructed an object rather than computing a result; 3 with no instrument failure: 0 honoured, 0 violated, 3 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/llm-in-the-loop-leveraging-large-language#ran","syntology_url":"https://syntology.ai/paper/2310.15100","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2310.15100"}},"official":{"repos":["sjdai/llm-thematic-analysis"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":3,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/cxr-llava-multimodal-large-language-model-for","slug":"cxr-llava-multimodal-large-language-model-for","title":"CXR-LLAVA: a multimodal large language model for interpreting chest X-ray images","date":"2023-10-22","arxiv_id":"2310.18341","repositories_listed":1,"syntology":{"n":3,"n_ran":2,"n_constructed":0,"n_ran_checked":2,"n_instrument":0,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":2,"n_pointer_only":3,"phrase":"2 ran (of which 0 constructed an object rather than computing a result; 2 with no instrument failure: 0 honoured, 0 violated, 2 with no contract checked; 0 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/cxr-llava-multimodal-large-language-model-for#ran","syntology_url":"https://syntology.ai/paper/2310.18341","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2310.18341"}},"official":{"repos":["ecofri/cxr_llava"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":0,"n_ran_no_instrument_failure":2,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/on-bilingual-lexicon-induction-with-large","slug":"on-bilingual-lexicon-induction-with-large","title":"On Bilingual Lexicon Induction with Large Language Models","date":"2023-10-21","arxiv_id":"2310.13995","repositories_listed":1,"syntology":{"n":4,"n_ran":3,"n_constructed":0,"n_ran_checked":3,"n_instrument":0,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":3,"n_pointer_only":0,"phrase":"3 ran (of which 0 constructed an object rather than computing a result; 3 with no instrument failure: 0 honoured, 0 violated, 3 with no contract checked; 0 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/on-bilingual-lexicon-induction-with-large#ran","syntology_url":"https://syntology.ai/paper/2310.13995","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2310.13995"}},"official":{"repos":["cambridgeltl/prompt4bli"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":3,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/democratizing-reasoning-ability-tailored","slug":"democratizing-reasoning-ability-tailored","title":"Democratizing Reasoning Ability: Tailored Learning from Large Language Model","date":"2023-10-20","arxiv_id":"2310.13332","repositories_listed":1,"syntology":{"n":8,"n_ran":5,"n_constructed":0,"n_ran_checked":5,"n_instrument":0,"n_unverified":3,"n_honours":0,"n_violates":0,"n_no_contract":5,"n_pointer_only":8,"phrase":"5 ran (of which 0 constructed an object rather than computing a result; 5 with no instrument failure: 0 honoured, 0 violated, 5 with no contract checked; 0 where Syntology's instrument failed) · 3 unverified","sample_list":"/paper/democratizing-reasoning-ability-tailored#ran","syntology_url":"https://syntology.ai/paper/2310.13332","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2310.13332"}},"official":{"repos":["raibows/learn-to-reason"],"state":"official (archive's flag): 5 ran","n_ran":5,"n_constructed":0,"n_ran_no_instrument_failure":5,"n_unverified":3,"ran_from_kinds":["official"]}}},{"url":"/paper/let-s-synthesize-step-by-step-iterative","slug":"let-s-synthesize-step-by-step-iterative","title":"Let's Synthesize Step by Step: Iterative Dataset Synthesis with Large Language Models by Extrapolating Errors from Small Models","date":"2023-10-20","arxiv_id":"2310.13671","repositories_listed":1,"syntology":{"n":12,"n_ran":7,"n_constructed":0,"n_ran_checked":7,"n_instrument":0,"n_unverified":5,"n_honours":0,"n_violates":0,"n_no_contract":7,"n_pointer_only":12,"phrase":"7 ran (of which 0 constructed an object rather than computing a result; 7 with no instrument failure: 0 honoured, 0 violated, 7 with no contract checked; 0 where Syntology's instrument failed) · 5 unverified","sample_list":"/paper/let-s-synthesize-step-by-step-iterative#ran","syntology_url":"https://syntology.ai/paper/2310.13671","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2310.13671"}},"official":{"repos":["rickyskywalker/synthesis_step-by-step_official"],"state":"official (archive's flag): 7 ran","n_ran":7,"n_constructed":0,"n_ran_no_instrument_failure":7,"n_unverified":5,"ran_from_kinds":["official"]}}},{"url":"/paper/loop-copilot-conducting-ai-ensembles-for","slug":"loop-copilot-conducting-ai-ensembles-for","title":"Loop Copilot: Conducting AI Ensembles for Music Generation and Iterative Editing","date":"2023-10-19","arxiv_id":"2310.12404","repositories_listed":1,"syntology":{"n":13,"n_ran":10,"n_constructed":0,"n_ran_checked":9,"n_instrument":1,"n_unverified":3,"n_honours":0,"n_violates":0,"n_no_contract":9,"n_pointer_only":4,"phrase":"10 ran (of which 0 constructed an object rather than computing a result; 9 with no instrument failure: 0 honoured, 0 violated, 9 with no contract checked; 1 where Syntology's instrument failed) · 3 unverified","sample_list":"/paper/loop-copilot-conducting-ai-ensembles-for#ran","syntology_url":"https://syntology.ai/paper/2310.12404","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2310.12404"}},"official":{"repos":["ldzhangyx/loop-copilot"],"state":"official (archive's flag): 10 ran","n_ran":10,"n_constructed":0,"n_ran_no_instrument_failure":9,"n_unverified":3,"ran_from_kinds":["official"]}}},{"url":"/paper/watermarking-llms-with-weight-quantization","slug":"watermarking-llms-with-weight-quantization","title":"Watermarking LLMs with Weight Quantization","date":"2023-10-17","arxiv_id":"2310.11237","repositories_listed":1,"syntology":{"n":10,"n_ran":1,"n_constructed":0,"n_ran_checked":1,"n_instrument":0,"n_unverified":9,"n_honours":0,"n_violates":0,"n_no_contract":1,"n_pointer_only":10,"phrase":"1 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 0 violated, 1 with no contract checked; 0 where Syntology's instrument failed) · 9 unverified","sample_list":"/paper/watermarking-llms-with-weight-quantization#ran","syntology_url":"https://syntology.ai/paper/2310.11237","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2310.11237"}},"official":{"repos":["twilight92z/quantize-watermark"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":9,"ran_from_kinds":["official"]}}},{"url":"/paper/evalcrafter-benchmarking-and-evaluating-large","slug":"evalcrafter-benchmarking-and-evaluating-large","title":"EvalCrafter: Benchmarking and Evaluating Large Video Generation Models","date":"2023-10-17","arxiv_id":"2310.11440","repositories_listed":1,"syntology":{"n":11,"n_ran":7,"n_constructed":0,"n_ran_checked":7,"n_instrument":0,"n_unverified":4,"n_honours":0,"n_violates":0,"n_no_contract":7,"n_pointer_only":11,"phrase":"7 ran (of which 0 constructed an object rather than computing a result; 7 with no instrument failure: 0 honoured, 0 violated, 7 with no contract checked; 0 where Syntology's instrument failed) · 4 unverified","sample_list":"/paper/evalcrafter-benchmarking-and-evaluating-large#ran","syntology_url":"https://syntology.ai/paper/2310.11440","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2310.11440"}},"official":{"repos":["EvalCrafter/EvalCrafter"],"state":"official (archive's flag): 7 ran","n_ran":7,"n_constructed":0,"n_ran_no_instrument_failure":7,"n_unverified":4,"ran_from_kinds":["official"]}}},{"url":"/paper/personalized-soups-personalized-large","slug":"personalized-soups-personalized-large","title":"Personalized Soups: Personalized Large Language Model Alignment via Post-hoc Parameter Merging","date":"2023-10-17","arxiv_id":"2310.11564","repositories_listed":1,"syntology":{"n":15,"n_ran":13,"n_constructed":0,"n_ran_checked":12,"n_instrument":1,"n_unverified":2,"n_honours":0,"n_violates":0,"n_no_contract":12,"n_pointer_only":15,"phrase":"13 ran (of which 0 constructed an object rather than computing a result; 12 with no instrument failure: 0 honoured, 0 violated, 12 with no contract checked; 1 where Syntology's instrument failed) · 2 unverified","sample_list":"/paper/personalized-soups-personalized-large#ran","syntology_url":"https://syntology.ai/paper/2310.11564","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2310.11564"}},"official":{"repos":["joeljang/rlphf"],"state":"official (archive's flag): 13 ran","n_ran":13,"n_constructed":0,"n_ran_no_instrument_failure":12,"n_unverified":2,"ran_from_kinds":["official"]}}},{"url":"/paper/weakly-supervised-fine-grained-scene-graph","slug":"weakly-supervised-fine-grained-scene-graph","title":"LLM4SGG: Large Language Models for Weakly Supervised Scene Graph Generation","date":"2023-10-16","arxiv_id":"2310.10404","repositories_listed":1,"syntology":{"n":4,"n_ran":4,"n_constructed":0,"n_ran_checked":4,"n_instrument":0,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":4,"n_pointer_only":4,"phrase":"4 ran (of which 0 constructed an object rather than computing a result; 4 with no instrument failure: 0 honoured, 0 violated, 4 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/weakly-supervised-fine-grained-scene-graph#ran","syntology_url":"https://syntology.ai/paper/2310.10404","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2310.10404"}},"official":{"repos":["rlqja1107/torch-LLM4SGG"],"state":"official (archive's flag): 4 ran","n_ran":4,"n_constructed":0,"n_ran_no_instrument_failure":4,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/large-language-model-empowered-agents-for","slug":"large-language-model-empowered-agents-for","title":"EconAgent: Large Language Model-Empowered Agents for Simulating Macroeconomic Activities","date":"2023-10-16","arxiv_id":"2310.10436","repositories_listed":1,"syntology":{"n":2,"n_ran":1,"n_constructed":0,"n_ran_checked":0,"n_instrument":1,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":0,"n_pointer_only":2,"phrase":"1 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 1 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/large-language-model-empowered-agents-for#ran","syntology_url":"https://syntology.ai/paper/2310.10436","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2310.10436"}},"official":{"repos":["tsinghua-fib-lab/acl24-econagent"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/llemma-an-open-language-model-for-mathematics","slug":"llemma-an-open-language-model-for-mathematics","title":"Llemma: An Open Language Model For Mathematics","date":"2023-10-16","arxiv_id":"2310.10631","repositories_listed":4,"syntology":{"n":8,"n_ran":7,"n_constructed":0,"n_ran_checked":7,"n_instrument":0,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":7,"n_pointer_only":0,"phrase":"7 ran (of which 0 constructed an object rather than computing a result; 7 with no instrument failure: 0 honoured, 0 violated, 7 with no contract checked; 0 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/llemma-an-open-language-model-for-mathematics#ran","syntology_url":"https://syntology.ai/paper/2310.10631","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2310.10631"}},"official":{"repos":["EleutherAI/math-lm","eleutherai/gpt-neox","wellecks/llmstep"],"state":"official (archive's flag): 6 ran","n_ran":6,"n_constructed":0,"n_ran_no_instrument_failure":6,"n_unverified":1,"ran_from_kinds":["listed","official"]}}},{"url":"/paper/enhancing-conversational-search-large","slug":"enhancing-conversational-search-large","title":"Enhancing Conversational Search: Large Language Model-Aided Informative Query Rewriting","date":"2023-10-15","arxiv_id":"2310.09716","repositories_listed":1,"syntology":{"n":5,"n_ran":5,"n_constructed":0,"n_ran_checked":5,"n_instrument":0,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":5,"n_pointer_only":5,"phrase":"5 ran (of which 0 constructed an object rather than computing a result; 5 with no instrument failure: 0 honoured, 0 violated, 5 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/enhancing-conversational-search-large#ran","syntology_url":"https://syntology.ai/paper/2310.09716","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2310.09716"}},"official":{"repos":["smartyfh/infocqr"],"state":"official (archive's flag): 5 ran","n_ran":5,"n_constructed":0,"n_ran_no_instrument_failure":5,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/film-fill-in-language-models-for-any-order","slug":"film-fill-in-language-models-for-any-order","title":"FiLM: Fill-in Language Models for Any-Order Generation","date":"2023-10-15","arxiv_id":"2310.09930","repositories_listed":1,"syntology":{"n":3,"n_ran":2,"n_constructed":0,"n_ran_checked":2,"n_instrument":0,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":2,"n_pointer_only":0,"phrase":"2 ran (of which 0 constructed an object rather than computing a result; 2 with no instrument failure: 0 honoured, 0 violated, 2 with no contract checked; 0 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/film-fill-in-language-models-for-any-order#ran","syntology_url":"https://syntology.ai/paper/2310.09930","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2310.09930"}},"official":{"repos":["shentianxiao/film"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":0,"n_ran_no_instrument_failure":2,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/minigpt-v2-large-language-model-as-a-unified","slug":"minigpt-v2-large-language-model-as-a-unified","title":"MiniGPT-v2: large language model as a unified interface for vision-language multi-task learning","date":"2023-10-14","arxiv_id":"2310.09478","repositories_listed":2,"syntology":{"n":3,"n_ran":3,"n_constructed":0,"n_ran_checked":0,"n_instrument":3,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":0,"n_pointer_only":1,"phrase":"3 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 3 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/minigpt-v2-large-language-model-as-a-unified#ran","syntology_url":"https://syntology.ai/paper/2310.09478","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2310.09478"}},"official":null}},{"url":"/paper/can-large-language-model-comprehend-ancient","slug":"can-large-language-model-comprehend-ancient","title":"Can Large Language Model Comprehend Ancient Chinese? A Preliminary Test on ACLUE","date":"2023-10-14","arxiv_id":"2310.09550","repositories_listed":1,"syntology":{"n":5,"n_ran":4,"n_constructed":0,"n_ran_checked":3,"n_instrument":1,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":3,"n_pointer_only":0,"phrase":"4 ran (of which 0 constructed an object rather than computing a result; 3 with no instrument failure: 0 honoured, 0 violated, 3 with no contract checked; 1 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/can-large-language-model-comprehend-ancient#ran","syntology_url":"https://syntology.ai/paper/2310.09550","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2310.09550"}},"official":{"repos":["isen-zhang/aclue"],"state":"official (archive's flag): 4 ran","n_ran":4,"n_constructed":0,"n_ran_no_instrument_failure":3,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/qilin-med-multi-stage-knowledge-injection","slug":"qilin-med-multi-stage-knowledge-injection","title":"Qilin-Med: Multi-stage Knowledge Injection Advanced Medical Large Language Model","date":"2023-10-13","arxiv_id":"2310.09089","repositories_listed":1,"syntology":{"n":6,"n_ran":5,"n_constructed":0,"n_ran_checked":1,"n_instrument":4,"n_unverified":1,"n_honours":1,"n_violates":0,"n_no_contract":0,"n_pointer_only":6,"phrase":"5 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 1 honoured, 0 violated, 0 with no contract checked; 4 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/qilin-med-multi-stage-knowledge-injection#ran","syntology_url":"https://syntology.ai/paper/2310.09089","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2310.09089"}},"official":{"repos":["williamliujl/Qilin-Med"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":1,"ran_from_kinds":["official","unlocated"]}}},{"url":"/paper/split-and-denoise-protect-large-language","slug":"split-and-denoise-protect-large-language","title":"Split-and-Denoise: Protect large language model inference with local differential privacy","date":"2023-10-13","arxiv_id":"2310.09130","repositories_listed":1,"syntology":{"n":4,"n_ran":4,"n_constructed":0,"n_ran_checked":4,"n_instrument":0,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":4,"n_pointer_only":4,"phrase":"4 ran (of which 0 constructed an object rather than computing a result; 4 with no instrument failure: 0 honoured, 0 violated, 4 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/split-and-denoise-protect-large-language#ran","syntology_url":"https://syntology.ai/paper/2310.09130","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2310.09130"}},"official":{"repos":["nusioraprivacy/eaas-privacy"],"state":"official (archive's flag): 4 ran","n_ran":4,"n_constructed":0,"n_ran_no_instrument_failure":4,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/large-language-models-for-scientific","slug":"large-language-models-for-scientific","title":"Large Language Models for Scientific Synthesis, Inference and Explanation","date":"2023-10-12","arxiv_id":"2310.07984","repositories_listed":1,"syntology":{"n":2,"n_ran":2,"n_constructed":0,"n_ran_checked":1,"n_instrument":1,"n_unverified":0,"n_honours":1,"n_violates":0,"n_no_contract":0,"n_pointer_only":0,"phrase":"2 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 1 honoured, 0 violated, 0 with no contract checked; 1 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/large-language-models-for-scientific#ran","syntology_url":"https://syntology.ai/paper/2310.07984","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2310.07984"}},"official":{"repos":["zyzisastudyreallyhardguy/llm4sd"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/towards-robust-multi-modal-reasoning-via","slug":"towards-robust-multi-modal-reasoning-via","title":"Towards Robust Multi-Modal Reasoning via Model Selection","date":"2023-10-12","arxiv_id":"2310.08446","repositories_listed":1,"syntology":{"n":6,"n_ran":3,"n_constructed":0,"n_ran_checked":3,"n_instrument":0,"n_unverified":3,"n_honours":0,"n_violates":0,"n_no_contract":3,"n_pointer_only":0,"phrase":"3 ran (of which 0 constructed an object rather than computing a result; 3 with no instrument failure: 0 honoured, 0 violated, 3 with no contract checked; 0 where Syntology's instrument failed) · 3 unverified","sample_list":"/paper/towards-robust-multi-modal-reasoning-via#ran","syntology_url":"https://syntology.ai/paper/2310.08446","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2310.08446"}},"official":{"repos":["LINs-lab/M3"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":3,"n_unverified":3,"ran_from_kinds":["official"]}}},{"url":"/paper/prometheus-inducing-fine-grained-evaluation","slug":"prometheus-inducing-fine-grained-evaluation","title":"Prometheus: Inducing Fine-grained Evaluation Capability in Language Models","date":"2023-10-12","arxiv_id":"2310.08491","repositories_listed":3,"syntology":{"n":9,"n_ran":4,"n_constructed":0,"n_ran_checked":3,"n_instrument":1,"n_unverified":5,"n_honours":0,"n_violates":0,"n_no_contract":3,"n_pointer_only":5,"phrase":"4 ran (of which 0 constructed an object rather than computing a result; 3 with no instrument failure: 0 honoured, 0 violated, 3 with no contract checked; 1 where Syntology's instrument failed) · 5 unverified","sample_list":"/paper/prometheus-inducing-fine-grained-evaluation#ran","syntology_url":"https://syntology.ai/paper/2310.08491","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2310.08491"}},"official":{"repos":["kaistAI/Prometheus"],"state":"official (archive's flag): 4 ran","n_ran":4,"n_constructed":0,"n_ran_no_instrument_failure":3,"n_unverified":5,"ran_from_kinds":["official"]}}},{"url":"/paper/cachegen-fast-context-loading-for-language","slug":"cachegen-fast-context-loading-for-language","title":"CacheGen: KV Cache Compression and Streaming for Fast Large Language Model Serving","date":"2023-10-11","arxiv_id":"2310.07240","repositories_listed":2,"syntology":{"n":2,"n_ran":2,"n_constructed":0,"n_ran_checked":1,"n_instrument":1,"n_unverified":0,"n_honours":1,"n_violates":0,"n_no_contract":0,"n_pointer_only":2,"phrase":"2 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 1 honoured, 0 violated, 0 with no contract checked; 1 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/cachegen-fast-context-loading-for-language#ran","syntology_url":"https://syntology.ai/paper/2310.07240","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2310.07240"}},"official":{"repos":["uchi-jcl/cachegen"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/ferret-refer-and-ground-anything-anywhere-at","slug":"ferret-refer-and-ground-anything-anywhere-at","title":"Ferret: Refer and Ground Anything Anywhere at Any Granularity","date":"2023-10-11","arxiv_id":"2310.07704","repositories_listed":2,"syntology":{"n":8,"n_ran":7,"n_constructed":0,"n_ran_checked":1,"n_instrument":6,"n_unverified":1,"n_honours":0,"n_violates":1,"n_no_contract":0,"n_pointer_only":8,"phrase":"7 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 1 violated, 0 with no contract checked; 6 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/ferret-refer-and-ground-anything-anywhere-at#ran","syntology_url":"https://syntology.ai/paper/2310.07704","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2310.07704"}},"official":{"repos":["apple/ml-ferret"],"state":"official (archive's flag): 7 ran","n_ran":7,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/we-are-what-we-repeatedly-do-inducing-and","slug":"we-are-what-we-repeatedly-do-inducing-and","title":"We are what we repeatedly do: Inducing and deploying habitual schemas in persona-based responses","date":"2023-10-10","arxiv_id":"2310.06245","repositories_listed":1,"syntology":{"n":7,"n_ran":5,"n_constructed":0,"n_ran_checked":5,"n_instrument":0,"n_unverified":2,"n_honours":0,"n_violates":0,"n_no_contract":5,"n_pointer_only":7,"phrase":"5 ran (of which 0 constructed an object rather than computing a result; 5 with no instrument failure: 0 honoured, 0 violated, 5 with no contract checked; 0 where Syntology's instrument failed) · 2 unverified","sample_list":"/paper/we-are-what-we-repeatedly-do-inducing-and#ran","syntology_url":"https://syntology.ai/paper/2310.06245","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2310.06245"}},"official":{"repos":["bkane2/habitual-response-generation"],"state":"official (archive's flag): 5 ran","n_ran":5,"n_constructed":0,"n_ran_no_instrument_failure":5,"n_unverified":2,"ran_from_kinds":["official"]}}},{"url":"/paper/making-large-language-models-perform-better","slug":"making-large-language-models-perform-better","title":"Making Large Language Models Perform Better in Knowledge Graph Completion","date":"2023-10-10","arxiv_id":"2310.06671","repositories_listed":1,"syntology":{"n":3,"n_ran":3,"n_constructed":0,"n_ran_checked":3,"n_instrument":0,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":3,"n_pointer_only":0,"phrase":"3 ran (of which 0 constructed an object rather than computing a result; 3 with no instrument failure: 0 honoured, 0 violated, 3 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/making-large-language-models-perform-better#ran","syntology_url":"https://syntology.ai/paper/2310.06671","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2310.06671"}},"official":{"repos":["zjukg/kopa"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":3,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/seer-a-knapsack-approach-to-exemplar","slug":"seer-a-knapsack-approach-to-exemplar","title":"SEER : A Knapsack approach to Exemplar Selection for In-Context HybridQA","date":"2023-10-10","arxiv_id":"2310.06675","repositories_listed":1,"syntology":{"n":16,"n_ran":6,"n_constructed":0,"n_ran_checked":5,"n_instrument":1,"n_unverified":10,"n_honours":2,"n_violates":0,"n_no_contract":3,"n_pointer_only":0,"phrase":"6 ran (of which 0 constructed an object rather than computing a result; 5 with no instrument failure: 2 honoured, 0 violated, 3 with no contract checked; 1 where Syntology's instrument failed) · 10 unverified","sample_list":"/paper/seer-a-knapsack-approach-to-exemplar#ran","syntology_url":"https://syntology.ai/paper/2310.06675","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2310.06675"}},"official":{"repos":["jtonglet/seer"],"state":"official (archive's flag): 6 ran","n_ran":6,"n_constructed":0,"n_ran_no_instrument_failure":5,"n_unverified":10,"ran_from_kinds":["official"]}}},{"url":"/paper/the-geometry-of-truth-emergent-linear","slug":"the-geometry-of-truth-emergent-linear","title":"The Geometry of Truth: Emergent Linear Structure in Large Language Model Representations of True/False Datasets","date":"2023-10-10","arxiv_id":"2310.06824","repositories_listed":1,"syntology":{"n":2,"n_ran":1,"n_constructed":0,"n_ran_checked":0,"n_instrument":1,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":0,"n_pointer_only":2,"phrase":"1 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 1 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/the-geometry-of-truth-emergent-linear#ran","syntology_url":"https://syntology.ai/paper/2310.06824","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2310.06824"}},"official":{"repos":["saprmarks/geometry-of-truth"],"state":"official: harvested, nothing ran","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":1,"ran_from_kinds":["unlocated"]}}},{"url":"/paper/graphllm-boosting-graph-reasoning-ability-of","slug":"graphllm-boosting-graph-reasoning-ability-of","title":"GraphLLM: Boosting Graph Reasoning Ability of Large Language Model","date":"2023-10-09","arxiv_id":"2310.05845","repositories_listed":1,"syntology":{"n":7,"n_ran":7,"n_constructed":0,"n_ran_checked":6,"n_instrument":1,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":6,"n_pointer_only":7,"phrase":"7 ran (of which 0 constructed an object rather than computing a result; 6 with no instrument failure: 0 honoured, 0 violated, 6 with no contract checked; 1 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/graphllm-boosting-graph-reasoning-ability-of#ran","syntology_url":"https://syntology.ai/paper/2310.05845","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2310.05845"}},"official":{"repos":["mistyreed63849/graph-llm"],"state":"official (archive's flag): 7 ran","n_ran":7,"n_constructed":0,"n_ran_no_instrument_failure":6,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/brainteaser-lateral-thinking-puzzles-for","slug":"brainteaser-lateral-thinking-puzzles-for","title":"BRAINTEASER: Lateral Thinking Puzzles for Large Language Models","date":"2023-10-08","arxiv_id":"2310.05057","repositories_listed":2,"syntology":{"n":7,"n_ran":7,"n_constructed":0,"n_ran_checked":4,"n_instrument":3,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":4,"n_pointer_only":3,"phrase":"7 ran (of which 0 constructed an object rather than computing a result; 4 with no instrument failure: 0 honoured, 0 violated, 4 with no contract checked; 3 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/brainteaser-lateral-thinking-puzzles-for#ran","syntology_url":"https://syntology.ai/paper/2310.05057","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2310.05057"}},"official":null}},{"url":"/paper/ureader-universal-ocr-free-visually-situated","slug":"ureader-universal-ocr-free-visually-situated","title":"UReader: Universal OCR-free Visually-situated Language Understanding with Multimodal Large Language Model","date":"2023-10-08","arxiv_id":"2310.05126","repositories_listed":1,"syntology":{"n":11,"n_ran":10,"n_constructed":0,"n_ran_checked":9,"n_instrument":1,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":9,"n_pointer_only":0,"phrase":"10 ran (of which 0 constructed an object rather than computing a result; 9 with no instrument failure: 0 honoured, 0 violated, 9 with no contract checked; 1 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/ureader-universal-ocr-free-visually-situated#ran","syntology_url":"https://syntology.ai/paper/2310.05126","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2310.05126"}},"official":{"repos":["lukeforeveryoung/ureader"],"state":"official (archive's flag): 10 ran","n_ran":10,"n_constructed":0,"n_ran_no_instrument_failure":9,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/instructdet-diversifying-referring-object","slug":"instructdet-diversifying-referring-object","title":"InstructDET: Diversifying Referring Object Detection with Generalized Instructions","date":"2023-10-08","arxiv_id":"2310.05136","repositories_listed":1,"syntology":{"n":1,"n_ran":1,"n_constructed":0,"n_ran_checked":1,"n_instrument":0,"n_unverified":0,"n_honours":1,"n_violates":0,"n_no_contract":0,"n_pointer_only":1,"phrase":"1 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 1 honoured, 0 violated, 0 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/instructdet-diversifying-referring-object#ran","syntology_url":"https://syntology.ai/paper/2310.05136","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2310.05136"}},"official":{"repos":["jyfenggogo/instructdet"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/chain-of-natural-language-inference-for","slug":"chain-of-natural-language-inference-for","title":"Chain of Natural Language Inference for Reducing Large Language Model Ungrounded Hallucinations","date":"2023-10-06","arxiv_id":"2310.03951","repositories_listed":1,"syntology":{"n":6,"n_ran":6,"n_constructed":0,"n_ran_checked":6,"n_instrument":0,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":6,"n_pointer_only":0,"phrase":"6 ran (of which 0 constructed an object rather than computing a result; 6 with no instrument failure: 0 honoured, 0 violated, 6 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/chain-of-natural-language-inference-for#ran","syntology_url":"https://syntology.ai/paper/2310.03951","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2310.03951"}},"official":{"repos":["microsoft/conli_hallucination"],"state":"official (archive's flag): 6 ran","n_ran":6,"n_constructed":0,"n_ran_no_instrument_failure":6,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/gollie-annotation-guidelines-improve-zero","slug":"gollie-annotation-guidelines-improve-zero","title":"GoLLIE: Annotation Guidelines improve Zero-Shot Information-Extraction","date":"2023-10-05","arxiv_id":"2310.03668","repositories_listed":1,"syntology":{"n":25,"n_ran":18,"n_constructed":2,"n_ran_checked":17,"n_instrument":1,"n_unverified":7,"n_honours":0,"n_violates":0,"n_no_contract":17,"n_pointer_only":0,"phrase":"18 ran (of which 2 constructed an object rather than computing a result; 17 with no instrument failure: 0 honoured, 0 violated, 17 with no contract checked; 1 where Syntology's instrument failed) · 7 unverified","sample_list":"/paper/gollie-annotation-guidelines-improve-zero#ran","syntology_url":"https://syntology.ai/paper/2310.03668","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2310.03668"}},"official":{"repos":["hitz-zentroa/gollie"],"state":"official (archive's flag): 18 ran","n_ran":18,"n_constructed":2,"n_ran_no_instrument_failure":17,"n_unverified":7,"ran_from_kinds":["official"]}}},{"url":"/paper/dynamic-llm-agent-network-an-llm-agent","slug":"dynamic-llm-agent-network-an-llm-agent","title":"A Dynamic LLM-Powered Agent Network for Task-Oriented Agent Collaboration","date":"2023-10-03","arxiv_id":"2310.02170","repositories_listed":1,"syntology":{"n":3,"n_ran":3,"n_constructed":0,"n_ran_checked":1,"n_instrument":2,"n_unverified":0,"n_honours":0,"n_violates":1,"n_no_contract":0,"n_pointer_only":0,"phrase":"3 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 1 violated, 0 with no contract checked; 2 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/dynamic-llm-agent-network-an-llm-agent#ran","syntology_url":"https://syntology.ai/paper/2310.02170","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2310.02170"}},"official":{"repos":["salt-nlp/dylan"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/l2mac-large-language-model-automatic-computer","slug":"l2mac-large-language-model-automatic-computer","title":"L2MAC: Large Language Model Automatic Computer for Extensive Code Generation","date":"2023-10-02","arxiv_id":"2310.02003","repositories_listed":2,"syntology":{"n":14,"n_ran":10,"n_constructed":0,"n_ran_checked":10,"n_instrument":0,"n_unverified":4,"n_honours":0,"n_violates":0,"n_no_contract":10,"n_pointer_only":0,"phrase":"10 ran (of which 0 constructed an object rather than computing a result; 10 with no instrument failure: 0 honoured, 0 violated, 10 with no contract checked; 0 where Syntology's instrument failed) · 4 unverified","sample_list":"/paper/l2mac-large-language-model-automatic-computer#ran","syntology_url":"https://syntology.ai/paper/2310.02003","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2310.02003"}},"official":{"repos":["samholt/l2mac","vanderschaarlab/l2mac"],"state":"official (archive's flag): 10 ran","n_ran":10,"n_constructed":0,"n_ran_no_instrument_failure":10,"n_unverified":4,"ran_from_kinds":["official"]}}},{"url":"/paper/adaptive-solver-framework-for-dynamic","slug":"adaptive-solver-framework-for-dynamic","title":"Adaptive-Solver Framework for Dynamic Strategy Selection in Large Language Model Reasoning","date":"2023-10-01","arxiv_id":"2310.01446","repositories_listed":1,"syntology":{"n":11,"n_ran":4,"n_constructed":0,"n_ran_checked":4,"n_instrument":0,"n_unverified":7,"n_honours":0,"n_violates":0,"n_no_contract":4,"n_pointer_only":11,"phrase":"4 ran (of which 0 constructed an object rather than computing a result; 4 with no instrument failure: 0 honoured, 0 violated, 4 with no contract checked; 0 where Syntology's instrument failed) · 7 unverified","sample_list":"/paper/adaptive-solver-framework-for-dynamic#ran","syntology_url":"https://syntology.ai/paper/2310.01446","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2310.01446"}},"official":{"repos":["john1226966735/adaptive-solver"],"state":"official (archive's flag): 4 ran","n_ran":4,"n_constructed":0,"n_ran_no_instrument_failure":4,"n_unverified":7,"ran_from_kinds":["official"]}}},{"url":"/paper/automatikz-text-guided-synthesis-of","slug":"automatikz-text-guided-synthesis-of","title":"AutomaTikZ: Text-Guided Synthesis of Scientific Vector Graphics with TikZ","date":"2023-09-30","arxiv_id":"2310.00367","repositories_listed":1,"syntology":{"n":2,"n_ran":1,"n_constructed":1,"n_ran_checked":1,"n_instrument":0,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":1,"n_pointer_only":0,"phrase":"1 ran (of which 1 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 0 violated, 1 with no contract checked; 0 where Syntology's instrument failed) · 1 unverified; the one sample that ran constructed an object rather than computing a result","sample_list":"/paper/automatikz-text-guided-synthesis-of#ran","syntology_url":"https://syntology.ai/paper/2310.00367","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2310.00367"}},"official":{"repos":["potamides/automatikz"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":1,"n_ran_no_instrument_failure":1,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/instructcv-instruction-tuned-text-to-image","slug":"instructcv-instruction-tuned-text-to-image","title":"InstructCV: Instruction-Tuned Text-to-Image Diffusion Models as Vision Generalists","date":"2023-09-30","arxiv_id":"2310.00390","repositories_listed":1,"syntology":{"n":12,"n_ran":5,"n_constructed":0,"n_ran_checked":5,"n_instrument":0,"n_unverified":7,"n_honours":0,"n_violates":0,"n_no_contract":5,"n_pointer_only":12,"phrase":"5 ran (of which 0 constructed an object rather than computing a result; 5 with no instrument failure: 0 honoured, 0 violated, 5 with no contract checked; 0 where Syntology's instrument failed) · 7 unverified","sample_list":"/paper/instructcv-instruction-tuned-text-to-image#ran","syntology_url":"https://syntology.ai/paper/2310.00390","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2310.00390"}},"official":{"repos":["AlaaLab/InstructCV"],"state":"official (archive's flag): 5 ran","n_ran":5,"n_constructed":0,"n_ran_no_instrument_failure":5,"n_unverified":7,"ran_from_kinds":["official"]}}},{"url":"/paper/alphazero-like-tree-search-can-guide-large","slug":"alphazero-like-tree-search-can-guide-large","title":"Alphazero-like Tree-Search can Guide Large Language Model Decoding and Training","date":"2023-09-29","arxiv_id":"2309.17179","repositories_listed":1,"syntology":{"n":10,"n_ran":8,"n_constructed":0,"n_ran_checked":8,"n_instrument":0,"n_unverified":2,"n_honours":1,"n_violates":0,"n_no_contract":7,"n_pointer_only":10,"phrase":"8 ran (of which 0 constructed an object rather than computing a result; 8 with no instrument failure: 1 honoured, 0 violated, 7 with no contract checked; 0 where Syntology's instrument failed) · 2 unverified","sample_list":"/paper/alphazero-like-tree-search-can-guide-large#ran","syntology_url":"https://syntology.ai/paper/2309.17179","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2309.17179"}},"official":{"repos":["waterhorse1/llm_tree_search"],"state":"official (archive's flag): 8 ran","n_ran":8,"n_constructed":0,"n_ran_no_instrument_failure":8,"n_unverified":2,"ran_from_kinds":["official"]}}},{"url":"/paper/motif-intrinsic-motivation-from-artificial","slug":"motif-intrinsic-motivation-from-artificial","title":"Motif: Intrinsic Motivation from Artificial Intelligence Feedback","date":"2023-09-29","arxiv_id":"2310.00166","repositories_listed":1,"syntology":{"n":5,"n_ran":3,"n_constructed":0,"n_ran_checked":3,"n_instrument":0,"n_unverified":2,"n_honours":0,"n_violates":0,"n_no_contract":3,"n_pointer_only":5,"phrase":"3 ran (of which 0 constructed an object rather than computing a result; 3 with no instrument failure: 0 honoured, 0 violated, 3 with no contract checked; 0 where Syntology's instrument failed) · 2 unverified","sample_list":"/paper/motif-intrinsic-motivation-from-artificial#ran","syntology_url":"https://syntology.ai/paper/2310.00166","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2310.00166"}},"official":{"repos":["facebookresearch/motif"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":3,"n_unverified":2,"ran_from_kinds":["official"]}}},{"url":"/paper/rllte-long-term-evolution-project-of","slug":"rllte-long-term-evolution-project-of","title":"RLLTE: Long-Term Evolution Project of Reinforcement Learning","date":"2023-09-28","arxiv_id":"2309.16382","repositories_listed":2,"syntology":{"n":5,"n_ran":4,"n_constructed":0,"n_ran_checked":4,"n_instrument":0,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":4,"n_pointer_only":0,"phrase":"4 ran (of which 0 constructed an object rather than computing a result; 4 with no instrument failure: 0 honoured, 0 violated, 4 with no contract checked; 0 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/rllte-long-term-evolution-project-of#ran","syntology_url":"https://syntology.ai/paper/2309.16382","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2309.16382"}},"official":{"repos":["RLE-Foundation/rllte"],"state":"official (archive's flag): 4 ran","n_ran":4,"n_constructed":0,"n_ran_no_instrument_failure":4,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/qwen-technical-report","slug":"qwen-technical-report","title":"Qwen Technical Report","date":"2023-09-28","arxiv_id":"2309.16609","repositories_listed":2,"syntology":{"n":4,"n_ran":2,"n_constructed":0,"n_ran_checked":0,"n_instrument":2,"n_unverified":2,"n_honours":0,"n_violates":0,"n_no_contract":0,"n_pointer_only":0,"phrase":"2 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 2 where Syntology's instrument failed) · 2 unverified","sample_list":"/paper/qwen-technical-report#ran","syntology_url":"https://syntology.ai/paper/2309.16609","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2309.16609"}},"official":{"repos":["QwenLM/Qwen-7B","qwenlm/qwen"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":2,"ran_from_kinds":["official"]}}},{"url":"/paper/mindgpt-interpreting-what-you-see-with-non","slug":"mindgpt-interpreting-what-you-see-with-non","title":"MindGPT: Interpreting What You See with Non-invasive Brain Recordings","date":"2023-09-27","arxiv_id":"2309.15729","repositories_listed":1,"syntology":{"n":7,"n_ran":3,"n_constructed":0,"n_ran_checked":3,"n_instrument":0,"n_unverified":4,"n_honours":0,"n_violates":0,"n_no_contract":3,"n_pointer_only":7,"phrase":"3 ran (of which 0 constructed an object rather than computing a result; 3 with no instrument failure: 0 honoured, 0 violated, 3 with no contract checked; 0 where Syntology's instrument failed) · 4 unverified","sample_list":"/paper/mindgpt-interpreting-what-you-see-with-non#ran","syntology_url":"https://syntology.ai/paper/2309.15729","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2309.15729"}},"official":{"repos":["jxuanc/mindgpt"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":3,"n_unverified":4,"ran_from_kinds":["official"]}}},{"url":"/paper/deepspeed-ulysses-system-optimizations-for","slug":"deepspeed-ulysses-system-optimizations-for","title":"DeepSpeed Ulysses: System Optimizations for Enabling Training of Extreme Long Sequence Transformer Models","date":"2023-09-25","arxiv_id":"2309.14509","repositories_listed":6,"syntology":{"n":2,"n_ran":2,"n_constructed":0,"n_ran_checked":1,"n_instrument":1,"n_unverified":0,"n_honours":1,"n_violates":0,"n_no_contract":0,"n_pointer_only":2,"phrase":"2 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 1 honoured, 0 violated, 0 with no contract checked; 1 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/deepspeed-ulysses-system-optimizations-for#ran","syntology_url":"https://syntology.ai/paper/2309.14509","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2309.14509"}},"official":null}},{"url":"/paper/code-soliloquies-for-accurate-calculations-in","slug":"code-soliloquies-for-accurate-calculations-in","title":"Code Soliloquies for Accurate Calculations in Large Language Models","date":"2023-09-21","arxiv_id":"2309.12161","repositories_listed":1,"syntology":{"n":4,"n_ran":3,"n_constructed":0,"n_ran_checked":0,"n_instrument":3,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":0,"n_pointer_only":4,"phrase":"3 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 3 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/code-soliloquies-for-accurate-calculations-in#ran","syntology_url":"https://syntology.ai/paper/2309.12161","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2309.12161"}},"official":{"repos":["luffycodes/tutorbot-spock-phys"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/llm-grounder-open-vocabulary-3d-visual","slug":"llm-grounder-open-vocabulary-3d-visual","title":"LLM-Grounder: Open-Vocabulary 3D Visual Grounding with Large Language Model as an Agent","date":"2023-09-21","arxiv_id":"2309.12311","repositories_listed":1,"syntology":{"n":5,"n_ran":5,"n_constructed":0,"n_ran_checked":5,"n_instrument":0,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":5,"n_pointer_only":3,"phrase":"5 ran (of which 0 constructed an object rather than computing a result; 5 with no instrument failure: 0 honoured, 0 violated, 5 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/llm-grounder-open-vocabulary-3d-visual#ran","syntology_url":"https://syntology.ai/paper/2309.12311","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2309.12311"}},"official":{"repos":["sled-group/chat-with-nerf"],"state":"official (archive's flag): 5 ran","n_ran":5,"n_constructed":0,"n_ran_no_instrument_failure":5,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/disc-lawllm-fine-tuning-large-language-models","slug":"disc-lawllm-fine-tuning-large-language-models","title":"DISC-LawLLM: Fine-tuning Large Language Models for Intelligent Legal Services","date":"2023-09-20","arxiv_id":"2309.11325","repositories_listed":2,"syntology":{"n":6,"n_ran":5,"n_constructed":0,"n_ran_checked":5,"n_instrument":0,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":5,"n_pointer_only":0,"phrase":"5 ran (of which 0 constructed an object rather than computing a result; 5 with no instrument failure: 0 honoured, 0 violated, 5 with no contract checked; 0 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/disc-lawllm-fine-tuning-large-language-models#ran","syntology_url":"https://syntology.ai/paper/2309.11325","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2309.11325"}},"official":{"repos":["fudandisc/disc-lawllm"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":3,"n_unverified":1,"ran_from_kinds":["listed","official"]}}},{"url":"/paper/exploring-self-reinforcement-for-improving","slug":"exploring-self-reinforcement-for-improving","title":"Exploring Iterative Enhancement for Improving Learnersourced Multiple-Choice Question Explanations with Large Language Models","date":"2023-09-19","arxiv_id":"2309.10444","repositories_listed":1,"syntology":{"n":2,"n_ran":1,"n_constructed":0,"n_ran_checked":1,"n_instrument":0,"n_unverified":1,"n_honours":0,"n_violates":1,"n_no_contract":0,"n_pointer_only":2,"phrase":"1 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 1 violated, 0 with no contract checked; 0 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/exploring-self-reinforcement-for-improving#ran","syntology_url":"https://syntology.ai/paper/2309.10444","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2309.10444"}},"official":{"repos":["strong-ai-lab/explanation-generation"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/exploring-the-impact-of-low-rank-adaptation","slug":"exploring-the-impact-of-low-rank-adaptation","title":"Exploring the impact of low-rank adaptation on the performance, efficiency, and regularization of RLHF","date":"2023-09-16","arxiv_id":"2309.09055","repositories_listed":1,"syntology":{"n":13,"n_ran":12,"n_constructed":0,"n_ran_checked":12,"n_instrument":0,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":12,"n_pointer_only":0,"phrase":"12 ran (of which 0 constructed an object rather than computing a result; 12 with no instrument failure: 0 honoured, 0 violated, 12 with no contract checked; 0 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/exploring-the-impact-of-low-rank-adaptation#ran","syntology_url":"https://syntology.ai/paper/2309.09055","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2309.09055"}},"official":{"repos":["simengsun/alpaca_farm_lora"],"state":"official (archive's flag): 12 ran","n_ran":12,"n_constructed":0,"n_ran_no_instrument_failure":12,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/find-what-you-want-learning-demand-1","slug":"find-what-you-want-learning-demand-1","title":"Find What You Want: Learning Demand-conditioned Object Attribute Space for Demand-driven Navigation","date":"2023-09-15","arxiv_id":"2309.08138","repositories_listed":1,"syntology":{"n":6,"n_ran":4,"n_constructed":3,"n_ran_checked":4,"n_instrument":0,"n_unverified":2,"n_honours":0,"n_violates":0,"n_no_contract":4,"n_pointer_only":6,"phrase":"4 ran (of which 3 constructed an object rather than computing a result; 4 with no instrument failure: 0 honoured, 0 violated, 4 with no contract checked; 0 where Syntology's instrument failed) · 2 unverified","sample_list":"/paper/find-what-you-want-learning-demand-1#ran","syntology_url":"https://syntology.ai/paper/2309.08138","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2309.08138"}},"official":{"repos":["whcpumpkin/demand-driven-navigation"],"state":"official (archive's flag): 4 ran","n_ran":4,"n_constructed":3,"n_ran_no_instrument_failure":4,"n_unverified":2,"ran_from_kinds":["official"]}}},{"url":"/paper/draft-verify-lossless-large-language-model","slug":"draft-verify-lossless-large-language-model","title":"Draft & Verify: Lossless Large Language Model Acceleration via Self-Speculative Decoding","date":"2023-09-15","arxiv_id":"2309.08168","repositories_listed":1,"syntology":{"n":1,"n_ran":1,"n_constructed":0,"n_ran_checked":0,"n_instrument":1,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":0,"n_pointer_only":0,"phrase":"1 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 1 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/draft-verify-lossless-large-language-model#ran","syntology_url":"https://syntology.ai/paper/2309.08168","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2309.08168"}},"official":{"repos":["dilab-zju/self-speculative-decoding"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/investlm-a-large-language-model-for","slug":"investlm-a-large-language-model-for","title":"InvestLM: A Large Language Model for Investment using Financial Domain Instruction Tuning","date":"2023-09-15","arxiv_id":"2309.13064","repositories_listed":1,"syntology":{"n":1,"n_ran":1,"n_constructed":0,"n_ran_checked":0,"n_instrument":1,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":0,"n_pointer_only":1,"phrase":"1 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 1 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/investlm-a-large-language-model-for#ran","syntology_url":"https://syntology.ai/paper/2309.13064","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2309.13064"}},"official":{"repos":["abacinlp/investlm"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/sib-200-a-simple-inclusive-and-big-evaluation","slug":"sib-200-a-simple-inclusive-and-big-evaluation","title":"SIB-200: A Simple, Inclusive, and Big Evaluation Dataset for Topic Classification in 200+ Languages and Dialects","date":"2023-09-14","arxiv_id":"2309.07445","repositories_listed":2,"syntology":{"n":3,"n_ran":3,"n_constructed":0,"n_ran_checked":0,"n_instrument":3,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":0,"n_pointer_only":0,"phrase":"3 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 3 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/sib-200-a-simple-inclusive-and-big-evaluation#ran","syntology_url":"https://syntology.ai/paper/2309.07445","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2309.07445"}},"official":{"repos":["dadelani/sib-200"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/unified-human-scene-interaction-via-prompted","slug":"unified-human-scene-interaction-via-prompted","title":"Unified Human-Scene Interaction via Prompted Chain-of-Contacts","date":"2023-09-14","arxiv_id":"2309.07918","repositories_listed":1,"syntology":{"n":4,"n_ran":3,"n_constructed":0,"n_ran_checked":2,"n_instrument":1,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":2,"n_pointer_only":4,"phrase":"3 ran (of which 0 constructed an object rather than computing a result; 2 with no instrument failure: 0 honoured, 0 violated, 2 with no contract checked; 1 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/unified-human-scene-interaction-via-prompted#ran","syntology_url":"https://syntology.ai/paper/2309.07918","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2309.07918"}},"official":{"repos":["openrobotlab/unihsi"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":2,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/trafficgpt-viewing-processing-and-interacting","slug":"trafficgpt-viewing-processing-and-interacting","title":"TrafficGPT: Viewing, Processing and Interacting with Traffic Foundation Models","date":"2023-09-13","arxiv_id":"2309.06719","repositories_listed":1,"syntology":{"n":5,"n_ran":4,"n_constructed":0,"n_ran_checked":4,"n_instrument":0,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":4,"n_pointer_only":5,"phrase":"4 ran (of which 0 constructed an object rather than computing a result; 4 with no instrument failure: 0 honoured, 0 violated, 4 with no contract checked; 0 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/trafficgpt-viewing-processing-and-interacting#ran","syntology_url":"https://syntology.ai/paper/2309.06719","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2309.06719"}},"official":{"repos":["lijlansg/trafficgpt"],"state":"official (archive's flag): 4 ran","n_ran":4,"n_constructed":0,"n_ran_no_instrument_failure":4,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/2309-06180","slug":"2309-06180","title":"Efficient Memory Management for Large Language Model Serving with PagedAttention","date":"2023-09-12","arxiv_id":"2309.06180","repositories_listed":7,"syntology":{"n":36,"n_ran":28,"n_constructed":0,"n_ran_checked":22,"n_instrument":6,"n_unverified":8,"n_honours":3,"n_violates":1,"n_no_contract":18,"n_pointer_only":11,"phrase":"28 ran (of which 0 constructed an object rather than computing a result; 22 with no instrument failure: 3 honoured, 1 violated, 18 with no contract checked; 6 where Syntology's instrument failed) · 8 unverified","sample_list":"/paper/2309-06180#ran","syntology_url":"https://syntology.ai/paper/2309.06180","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2309.06180"}},"official":{"repos":["vllm-project/vllm"],"state":"community repositories only","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["listed"]}}},{"url":"/paper/leveraging-large-language-models-for-1","slug":"leveraging-large-language-models-for-1","title":"Leveraging Large Language Models for Automated Dialogue Analysis","date":"2023-09-12","arxiv_id":"2309.06490","repositories_listed":1,"syntology":{"n":5,"n_ran":2,"n_constructed":0,"n_ran_checked":2,"n_instrument":0,"n_unverified":3,"n_honours":0,"n_violates":0,"n_no_contract":2,"n_pointer_only":5,"phrase":"2 ran (of which 0 constructed an object rather than computing a result; 2 with no instrument failure: 0 honoured, 0 violated, 2 with no contract checked; 0 where Syntology's instrument failed) · 3 unverified","sample_list":"/paper/leveraging-large-language-models-for-1#ran","syntology_url":"https://syntology.ai/paper/2309.06490","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2309.06490"}},"official":{"repos":["emorynlp/gpt-abceval"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":0,"n_ran_no_instrument_failure":2,"n_unverified":3,"ran_from_kinds":["official"]}}},{"url":"/paper/unified-language-vision-pretraining-with","slug":"unified-language-vision-pretraining-with","title":"Unified Language-Vision Pretraining in LLM with Dynamic Discrete Visual Tokenization","date":"2023-09-09","arxiv_id":"2309.04669","repositories_listed":1,"syntology":{"n":1,"n_ran":1,"n_constructed":0,"n_ran_checked":0,"n_instrument":1,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":0,"n_pointer_only":1,"phrase":"1 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 1 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/unified-language-vision-pretraining-with#ran","syntology_url":"https://syntology.ai/paper/2309.04669","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2309.04669"}},"official":{"repos":["jy0205/lavit"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/publicly-shareable-clinical-large-language","slug":"publicly-shareable-clinical-large-language","title":"Publicly Shareable Clinical Large Language Model Built on Synthetic Clinical Notes","date":"2023-09-01","arxiv_id":"2309.00237","repositories_listed":1,"syntology":{"n":1,"n_ran":1,"n_constructed":0,"n_ran_checked":0,"n_instrument":1,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":0,"n_pointer_only":1,"phrase":"1 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 1 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/publicly-shareable-clinical-large-language#ran","syntology_url":"https://syntology.ai/paper/2309.00237","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2309.00237"}},"official":{"repos":["starmpcc/asclepius"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/point-bind-point-llm-aligning-point-cloud","slug":"point-bind-point-llm-aligning-point-cloud","title":"Point-Bind & Point-LLM: Aligning Point Cloud with Multi-modality for 3D Understanding, Generation, and Instruction Following","date":"2023-09-01","arxiv_id":"2309.00615","repositories_listed":5,"syntology":{"n":20,"n_ran":15,"n_constructed":0,"n_ran_checked":11,"n_instrument":4,"n_unverified":5,"n_honours":2,"n_violates":1,"n_no_contract":8,"n_pointer_only":15,"phrase":"15 ran (of which 0 constructed an object rather than computing a result; 11 with no instrument failure: 2 honoured, 1 violated, 8 with no contract checked; 4 where Syntology's instrument failed) · 5 unverified","sample_list":"/paper/point-bind-point-llm-aligning-point-cloud#ran","syntology_url":"https://syntology.ai/paper/2309.00615","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2309.00615"}},"official":{"repos":["ziyuguo99/point-bind_point-llm"],"state":"official (archive's flag): 10 ran","n_ran":10,"n_constructed":0,"n_ran_no_instrument_failure":6,"n_unverified":2,"ran_from_kinds":["listed","official"]}}},{"url":"/paper/fire-food-image-to-recipe-generation","slug":"fire-food-image-to-recipe-generation","title":"FIRE: Food Image to REcipe generation","date":"2023-08-28","arxiv_id":"2308.14391","repositories_listed":1,"syntology":{"n":16,"n_ran":12,"n_constructed":2,"n_ran_checked":10,"n_instrument":2,"n_unverified":4,"n_honours":0,"n_violates":0,"n_no_contract":10,"n_pointer_only":16,"phrase":"12 ran (of which 2 constructed an object rather than computing a result; 10 with no instrument failure: 0 honoured, 0 violated, 10 with no contract checked; 2 where Syntology's instrument failed) · 4 unverified","sample_list":"/paper/fire-food-image-to-recipe-generation#ran","syntology_url":"https://syntology.ai/paper/2308.14391","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2308.14391"}},"official":{"repos":["prateekchhikara/fire"],"state":"official (archive's flag): 12 ran","n_ran":12,"n_constructed":2,"n_ran_no_instrument_failure":10,"n_unverified":4,"ran_from_kinds":["official"]}}},{"url":"/paper/covr-learning-composed-video-retrieval-from","slug":"covr-learning-composed-video-retrieval-from","title":"CoVR-2: Automatic Data Construction for Composed Video Retrieval","date":"2023-08-28","arxiv_id":"2308.14746","repositories_listed":1,"syntology":{"n":1,"n_ran":1,"n_constructed":0,"n_ran_checked":0,"n_instrument":1,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":0,"n_pointer_only":0,"phrase":"1 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 1 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/covr-learning-composed-video-retrieval-from#ran","syntology_url":"https://syntology.ai/paper/2308.14746","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2308.14746"}},"official":{"repos":["lucas-ventura/CoVR"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/omniquant-omnidirectionally-calibrated","slug":"omniquant-omnidirectionally-calibrated","title":"OmniQuant: Omnidirectionally Calibrated Quantization for Large Language Models","date":"2023-08-25","arxiv_id":"2308.13137","repositories_listed":2,"syntology":{"n":16,"n_ran":10,"n_constructed":1,"n_ran_checked":8,"n_instrument":2,"n_unverified":6,"n_honours":0,"n_violates":0,"n_no_contract":8,"n_pointer_only":9,"phrase":"10 ran (of which 1 constructed an object rather than computing a result; 8 with no instrument failure: 0 honoured, 0 violated, 8 with no contract checked; 2 where Syntology's instrument failed) · 6 unverified","sample_list":"/paper/omniquant-omnidirectionally-calibrated#ran","syntology_url":"https://syntology.ai/paper/2308.13137","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2308.13137"}},"official":{"repos":["opengvlab/omniquant"],"state":"official (archive's flag): 9 ran","n_ran":9,"n_constructed":0,"n_ran_no_instrument_failure":7,"n_unverified":6,"ran_from_kinds":["listed","official"]}}},{"url":"/paper/scieval-a-multi-level-large-language-model","slug":"scieval-a-multi-level-large-language-model","title":"SciEval: A Multi-Level Large Language Model Evaluation Benchmark for Scientific Research","date":"2023-08-25","arxiv_id":"2308.13149","repositories_listed":2,"syntology":{"n":2,"n_ran":2,"n_constructed":0,"n_ran_checked":2,"n_instrument":0,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":2,"n_pointer_only":2,"phrase":"2 ran (of which 0 constructed an object rather than computing a result; 2 with no instrument failure: 0 honoured, 0 violated, 2 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/scieval-a-multi-level-large-language-model#ran","syntology_url":"https://syntology.ai/paper/2308.13149","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2308.13149"}},"official":{"repos":["opendfm/bai-scieval","opendfm/scieval"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":0,"n_ran_no_instrument_failure":2,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/large-language-model-as-autonomous-decision","slug":"large-language-model-as-autonomous-decision","title":"Rational Decision-Making Agent with Internalized Utility Judgment","date":"2023-08-24","arxiv_id":"2308.12519","repositories_listed":0,"syntology":{"n":15,"n_ran":11,"n_constructed":2,"n_ran_checked":8,"n_instrument":3,"n_unverified":4,"n_honours":4,"n_violates":1,"n_no_contract":3,"n_pointer_only":15,"phrase":"11 ran (of which 2 constructed an object rather than computing a result; 8 with no instrument failure: 4 honoured, 1 violated, 3 with no contract checked; 3 where Syntology's instrument failed) · 4 unverified","sample_list":"/paper/large-language-model-as-autonomous-decision#ran","syntology_url":"https://syntology.ai/paper/2308.12519","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2308.12519"}},"official":null}},{"url":"/paper/large-multilingual-models-pivot-zero-shot","slug":"large-multilingual-models-pivot-zero-shot","title":"Large Multilingual Models Pivot Zero-Shot Multimodal Learning across Languages","date":"2023-08-23","arxiv_id":"2308.12038","repositories_listed":2,"syntology":{"n":7,"n_ran":6,"n_constructed":0,"n_ran_checked":6,"n_instrument":0,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":6,"n_pointer_only":7,"phrase":"6 ran (of which 0 constructed an object rather than computing a result; 6 with no instrument failure: 0 honoured, 0 violated, 6 with no contract checked; 0 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/large-multilingual-models-pivot-zero-shot#ran","syntology_url":"https://syntology.ai/paper/2308.12038","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2308.12038"}},"official":{"repos":["openbmb/viscpm"],"state":"official (archive's flag): 6 ran","n_ran":6,"n_constructed":0,"n_ran_no_instrument_failure":6,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/rella-retrieval-enhanced-large-language","slug":"rella-retrieval-enhanced-large-language","title":"ReLLa: Retrieval-enhanced Large Language Models for Lifelong Sequential Behavior Comprehension in Recommendation","date":"2023-08-22","arxiv_id":"2308.11131","repositories_listed":1,"syntology":{"n":9,"n_ran":8,"n_constructed":0,"n_ran_checked":8,"n_instrument":0,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":8,"n_pointer_only":9,"phrase":"8 ran (of which 0 constructed an object rather than computing a result; 8 with no instrument failure: 0 honoured, 0 violated, 8 with no contract checked; 0 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/rella-retrieval-enhanced-large-language#ran","syntology_url":"https://syntology.ai/paper/2308.11131","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2308.11131"}},"official":{"repos":["lavieenrose365/rella"],"state":"official (archive's flag): 8 ran","n_ran":8,"n_constructed":0,"n_ran_no_instrument_failure":8,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/music-understanding-llama-advancing-text-to","slug":"music-understanding-llama-advancing-text-to","title":"Music Understanding LLaMA: Advancing Text-to-Music Generation with Question Answering and Captioning","date":"2023-08-22","arxiv_id":"2308.11276","repositories_listed":3,"syntology":{"n":4,"n_ran":3,"n_constructed":0,"n_ran_checked":1,"n_instrument":2,"n_unverified":1,"n_honours":0,"n_violates":1,"n_no_contract":0,"n_pointer_only":4,"phrase":"3 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 1 violated, 0 with no contract checked; 2 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/music-understanding-llama-advancing-text-to#ran","syntology_url":"https://syntology.ai/paper/2308.11276","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2308.11276"}},"official":{"repos":["crypto-code/mu-llama"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/a-study-on-robustness-and-reliability-of","slug":"a-study-on-robustness-and-reliability-of","title":"Can ChatGPT replace StackOverflow? A Study on Robustness and Reliability of Large Language Model Code Generation","date":"2023-08-20","arxiv_id":"2308.10335","repositories_listed":1,"syntology":{"n":5,"n_ran":5,"n_constructed":0,"n_ran_checked":5,"n_instrument":0,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":5,"n_pointer_only":5,"phrase":"5 ran (of which 0 constructed an object rather than computing a result; 5 with no instrument failure: 0 honoured, 0 violated, 5 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/a-study-on-robustness-and-reliability-of#ran","syntology_url":"https://syntology.ai/paper/2308.10335","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2308.10335"}},"official":{"repos":["floridsleeves/robustapi"],"state":"official (archive's flag): 5 ran","n_ran":5,"n_constructed":0,"n_ran_no_instrument_failure":5,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/chatharuhi-reviving-anime-character-in","slug":"chatharuhi-reviving-anime-character-in","title":"ChatHaruhi: Reviving Anime Character in Reality via Large Language Model","date":"2023-08-18","arxiv_id":"2308.09597","repositories_listed":1,"syntology":{"n":1,"n_ran":1,"n_constructed":0,"n_ran_checked":0,"n_instrument":1,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":0,"n_pointer_only":0,"phrase":"1 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 1 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/chatharuhi-reviving-anime-character-in#ran","syntology_url":"https://syntology.ai/paper/2308.09597","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2308.09597"}},"official":{"repos":["LC1332/Chat-Haruhi-Suzumiya"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/beam-retrieval-general-end-to-end-retrieval","slug":"beam-retrieval-general-end-to-end-retrieval","title":"End-to-End Beam Retrieval for Multi-Hop Question Answering","date":"2023-08-17","arxiv_id":"2308.08973","repositories_listed":3,"syntology":{"n":13,"n_ran":10,"n_constructed":0,"n_ran_checked":9,"n_instrument":1,"n_unverified":3,"n_honours":0,"n_violates":0,"n_no_contract":9,"n_pointer_only":2,"phrase":"10 ran (of which 0 constructed an object rather than computing a result; 9 with no instrument failure: 0 honoured, 0 violated, 9 with no contract checked; 1 where Syntology's instrument failed) · 3 unverified","sample_list":"/paper/beam-retrieval-general-end-to-end-retrieval#ran","syntology_url":"https://syntology.ai/paper/2308.08973","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2308.08973"}},"official":{"repos":["Alab-NII/2wikimultihop","canghongjian/beam_retriever"],"state":"official (archive's flag): 10 ran","n_ran":10,"n_constructed":0,"n_ran_no_instrument_failure":9,"n_unverified":3,"ran_from_kinds":["official"]}}},{"url":"/paper/mindmap-knowledge-graph-prompting-sparks","slug":"mindmap-knowledge-graph-prompting-sparks","title":"MindMap: Knowledge Graph Prompting Sparks Graph of Thoughts in Large Language Models","date":"2023-08-17","arxiv_id":"2308.09729","repositories_listed":1,"syntology":{"n":8,"n_ran":6,"n_constructed":0,"n_ran_checked":6,"n_instrument":0,"n_unverified":2,"n_honours":0,"n_violates":0,"n_no_contract":6,"n_pointer_only":8,"phrase":"6 ran (of which 0 constructed an object rather than computing a result; 6 with no instrument failure: 0 honoured, 0 violated, 6 with no contract checked; 0 where Syntology's instrument failed) · 2 unverified","sample_list":"/paper/mindmap-knowledge-graph-prompting-sparks#ran","syntology_url":"https://syntology.ai/paper/2308.09729","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2308.09729"}},"official":{"repos":["wyl-willing/MindMap"],"state":"official (archive's flag): 6 ran","n_ran":6,"n_constructed":0,"n_ran_no_instrument_failure":6,"n_unverified":2,"ran_from_kinds":["official"]}}},{"url":"/paper/test-text-prototype-aligned-embedding-to","slug":"test-text-prototype-aligned-embedding-to","title":"TEST: Text Prototype Aligned Embedding to Activate LLM's Ability for Time Series","date":"2023-08-16","arxiv_id":"2308.08241","repositories_listed":1,"syntology":{"n":11,"n_ran":9,"n_constructed":0,"n_ran_checked":9,"n_instrument":0,"n_unverified":2,"n_honours":0,"n_violates":0,"n_no_contract":9,"n_pointer_only":11,"phrase":"9 ran (of which 0 constructed an object rather than computing a result; 9 with no instrument failure: 0 honoured, 0 violated, 9 with no contract checked; 0 where Syntology's instrument failed) · 2 unverified","sample_list":"/paper/test-text-prototype-aligned-embedding-to#ran","syntology_url":"https://syntology.ai/paper/2308.08241","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2308.08241"}},"official":{"repos":["scxsunchenxi/test"],"state":"official (archive's flag): 9 ran","n_ran":9,"n_constructed":0,"n_ran_no_instrument_failure":9,"n_unverified":2,"ran_from_kinds":["official"]}}},{"url":"/paper/ternary-singular-value-decomposition-as-a","slug":"ternary-singular-value-decomposition-as-a","title":"Ternary Singular Value Decomposition as a Better Parameterized Form in Linear Mapping","date":"2023-08-15","arxiv_id":"2308.07641","repositories_listed":1,"syntology":{"n":3,"n_ran":3,"n_constructed":0,"n_ran_checked":0,"n_instrument":3,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":0,"n_pointer_only":0,"phrase":"3 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 3 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/ternary-singular-value-decomposition-as-a#ran","syntology_url":"https://syntology.ai/paper/2308.07641","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2308.07641"}},"official":{"repos":["ozzzp/ternary_decompose"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/git-mol-a-multi-modal-large-language-model","slug":"git-mol-a-multi-modal-large-language-model","title":"GIT-Mol: A Multi-modal Large Language Model for Molecular Science with Graph, Image, and Text","date":"2023-08-14","arxiv_id":"2308.06911","repositories_listed":1,"syntology":{"n":1,"n_ran":1,"n_constructed":0,"n_ran_checked":0,"n_instrument":1,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":0,"n_pointer_only":0,"phrase":"1 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 1 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/git-mol-a-multi-modal-large-language-model#ran","syntology_url":"https://syntology.ai/paper/2308.06911","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2308.06911"}},"official":{"repos":["ai-hpc-research-team/git-mol"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/rtllm-an-open-source-benchmark-for-design-rtl","slug":"rtllm-an-open-source-benchmark-for-design-rtl","title":"RTLLM: An Open-Source Benchmark for Design RTL Generation with Large Language Model","date":"2023-08-10","arxiv_id":"2308.05345","repositories_listed":1,"syntology":{"n":3,"n_ran":2,"n_constructed":0,"n_ran_checked":1,"n_instrument":1,"n_unverified":1,"n_honours":1,"n_violates":0,"n_no_contract":0,"n_pointer_only":0,"phrase":"2 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 1 honoured, 0 violated, 0 with no contract checked; 1 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/rtllm-an-open-source-benchmark-for-design-rtl#ran","syntology_url":"https://syntology.ai/paper/2308.05345","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2308.05345"}},"official":{"repos":["hkust-zhiyao/rtllm"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/esrl-efficient-sampling-based-reinforcement","slug":"esrl-efficient-sampling-based-reinforcement","title":"ESRL: Efficient Sampling-based Reinforcement Learning for Sequence Generation","date":"2023-08-04","arxiv_id":"2308.02223","repositories_listed":2,"syntology":{"n":14,"n_ran":12,"n_constructed":0,"n_ran_checked":11,"n_instrument":1,"n_unverified":2,"n_honours":0,"n_violates":0,"n_no_contract":11,"n_pointer_only":3,"phrase":"12 ran (of which 0 constructed an object rather than computing a result; 11 with no instrument failure: 0 honoured, 0 violated, 11 with no contract checked; 1 where Syntology's instrument failed) · 2 unverified","sample_list":"/paper/esrl-efficient-sampling-based-reinforcement#ran","syntology_url":"https://syntology.ai/paper/2308.02223","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2308.02223"}},"official":{"repos":["wangclnlp/DeepSpeed-Chat-Extension"],"state":"official (archive's flag): 12 ran","n_ran":12,"n_constructed":0,"n_ran_no_instrument_failure":11,"n_unverified":2,"ran_from_kinds":["official"]}}},{"url":"/paper/lp-musiccaps-llm-based-pseudo-music","slug":"lp-musiccaps-llm-based-pseudo-music","title":"LP-MusicCaps: LLM-Based Pseudo Music Captioning","date":"2023-07-31","arxiv_id":"2307.16372","repositories_listed":2,"syntology":{"n":7,"n_ran":7,"n_constructed":0,"n_ran_checked":7,"n_instrument":0,"n_unverified":0,"n_honours":1,"n_violates":0,"n_no_contract":6,"n_pointer_only":4,"phrase":"7 ran (of which 0 constructed an object rather than computing a result; 7 with no instrument failure: 1 honoured, 0 violated, 6 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/lp-musiccaps-llm-based-pseudo-music#ran","syntology_url":"https://syntology.ai/paper/2307.16372","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2307.16372"}},"official":{"repos":["seungheondoh/lp-music-caps"],"state":"official (archive's flag): 4 ran","n_ran":4,"n_constructed":0,"n_ran_no_instrument_failure":4,"n_unverified":0,"ran_from_kinds":["listed","official"]}}},{"url":"/paper/scaling-transnormer-to-175-billion-parameters","slug":"scaling-transnormer-to-175-billion-parameters","title":"TransNormerLLM: A Faster and Better Large Language Model with Improved TransNormer","date":"2023-07-27","arxiv_id":"2307.14995","repositories_listed":2,"syntology":{"n":5,"n_ran":3,"n_constructed":0,"n_ran_checked":1,"n_instrument":2,"n_unverified":2,"n_honours":1,"n_violates":0,"n_no_contract":0,"n_pointer_only":3,"phrase":"3 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 1 honoured, 0 violated, 0 with no contract checked; 2 where Syntology's instrument failed) · 2 unverified","sample_list":"/paper/scaling-transnormer-to-175-billion-parameters#ran","syntology_url":"https://syntology.ai/paper/2307.14995","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2307.14995"}},"official":{"repos":["opennlplab/transnormerllm"],"state":"community repositories only","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["listed"]}}},{"url":"/paper/outfox-llm-generated-essay-detection-through","slug":"outfox-llm-generated-essay-detection-through","title":"OUTFOX: LLM-Generated Essay Detection Through In-Context Learning with Adversarially Generated Examples","date":"2023-07-21","arxiv_id":"2307.11729","repositories_listed":1,"syntology":{"n":8,"n_ran":6,"n_constructed":0,"n_ran_checked":5,"n_instrument":1,"n_unverified":2,"n_honours":0,"n_violates":1,"n_no_contract":4,"n_pointer_only":1,"phrase":"6 ran (of which 0 constructed an object rather than computing a result; 5 with no instrument failure: 0 honoured, 1 violated, 4 with no contract checked; 1 where Syntology's instrument failed) · 2 unverified","sample_list":"/paper/outfox-llm-generated-essay-detection-through#ran","syntology_url":"https://syntology.ai/paper/2307.11729","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2307.11729"}},"official":{"repos":["ryuryukke/OUTFOX"],"state":"official (archive's flag): 6 ran","n_ran":6,"n_constructed":0,"n_ran_no_instrument_failure":5,"n_unverified":2,"ran_from_kinds":["official"]}}},{"url":"/paper/scibench-evaluating-college-level-scientific","slug":"scibench-evaluating-college-level-scientific","title":"SciBench: Evaluating College-Level Scientific Problem-Solving Abilities of Large Language Models","date":"2023-07-20","arxiv_id":"2307.10635","repositories_listed":1,"syntology":{"n":13,"n_ran":12,"n_constructed":0,"n_ran_checked":11,"n_instrument":1,"n_unverified":1,"n_honours":0,"n_violates":1,"n_no_contract":10,"n_pointer_only":2,"phrase":"12 ran (of which 0 constructed an object rather than computing a result; 11 with no instrument failure: 0 honoured, 1 violated, 10 with no contract checked; 1 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/scibench-evaluating-college-level-scientific#ran","syntology_url":"https://syntology.ai/paper/2307.10635","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2307.10635"}},"official":{"repos":["mandyyyyii/scibench"],"state":"official (archive's flag): 12 ran","n_ran":12,"n_constructed":0,"n_ran_no_instrument_failure":11,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/how-is-chatgpt-s-behavior-changing-over-time","slug":"how-is-chatgpt-s-behavior-changing-over-time","title":"How is ChatGPT's behavior changing over time?","date":"2023-07-18","arxiv_id":"2307.09009","repositories_listed":4,"syntology":{"n":6,"n_ran":6,"n_constructed":0,"n_ran_checked":4,"n_instrument":2,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":4,"n_pointer_only":5,"phrase":"6 ran (of which 0 constructed an object rather than computing a result; 4 with no instrument failure: 0 honoured, 0 violated, 4 with no contract checked; 2 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/how-is-chatgpt-s-behavior-changing-over-time#ran","syntology_url":"https://syntology.ai/paper/2307.09009","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2307.09009"}},"official":{"repos":["lchen001/llmdrift"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["listed","official"]}}},{"url":"/paper/language-conditioned-traffic-generation","slug":"language-conditioned-traffic-generation","title":"Language Conditioned Traffic Generation","date":"2023-07-16","arxiv_id":"2307.07947","repositories_listed":1,"syntology":{"n":8,"n_ran":7,"n_constructed":0,"n_ran_checked":7,"n_instrument":0,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":7,"n_pointer_only":0,"phrase":"7 ran (of which 0 constructed an object rather than computing a result; 7 with no instrument failure: 0 honoured, 0 violated, 7 with no contract checked; 0 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/language-conditioned-traffic-generation#ran","syntology_url":"https://syntology.ai/paper/2307.07947","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2307.07947"}},"official":{"repos":["Ariostgx/lctgen"],"state":"official (archive's flag): 7 ran","n_ran":7,"n_constructed":0,"n_ran_no_instrument_failure":7,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/coupling-large-language-models-with-logic","slug":"coupling-large-language-models-with-logic","title":"Coupling Large Language Models with Logic Programming for Robust and General Reasoning from Text","date":"2023-07-15","arxiv_id":"2307.07696","repositories_listed":1,"syntology":{"n":9,"n_ran":9,"n_constructed":0,"n_ran_checked":9,"n_instrument":0,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":9,"n_pointer_only":9,"phrase":"9 ran (of which 0 constructed an object rather than computing a result; 9 with no instrument failure: 0 honoured, 0 violated, 9 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/coupling-large-language-models-with-logic#ran","syntology_url":"https://syntology.ai/paper/2307.07696","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2307.07696"}},"official":{"repos":["azreasoners/llm-asp"],"state":"official (archive's flag): 9 ran","n_ran":9,"n_constructed":0,"n_ran_no_instrument_failure":9,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/think-on-graph-deep-and-responsible-reasoning","slug":"think-on-graph-deep-and-responsible-reasoning","title":"Think-on-Graph: Deep and Responsible Reasoning of Large Language Model on Knowledge Graph","date":"2023-07-15","arxiv_id":"2307.07697","repositories_listed":3,"syntology":{"n":16,"n_ran":12,"n_constructed":0,"n_ran_checked":10,"n_instrument":2,"n_unverified":4,"n_honours":1,"n_violates":1,"n_no_contract":8,"n_pointer_only":15,"phrase":"12 ran (of which 0 constructed an object rather than computing a result; 10 with no instrument failure: 1 honoured, 1 violated, 8 with no contract checked; 2 where Syntology's instrument failed) · 4 unverified","sample_list":"/paper/think-on-graph-deep-and-responsible-reasoning#ran","syntology_url":"https://syntology.ai/paper/2307.07697","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2307.07697"}},"official":{"repos":["gasolsun36/tog","idea-finai/tog"],"state":"official (archive's flag): 11 ran","n_ran":11,"n_constructed":0,"n_ran_no_instrument_failure":9,"n_unverified":4,"ran_from_kinds":["community","official"]}}},{"url":"/paper/in-context-autoencoder-for-context","slug":"in-context-autoencoder-for-context","title":"In-context Autoencoder for Context Compression in a Large Language Model","date":"2023-07-13","arxiv_id":"2307.06945","repositories_listed":2,"syntology":{"n":6,"n_ran":6,"n_constructed":0,"n_ran_checked":3,"n_instrument":3,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":3,"n_pointer_only":0,"phrase":"6 ran (of which 0 constructed an object rather than computing a result; 3 with no instrument failure: 0 honoured, 0 violated, 3 with no contract checked; 3 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/in-context-autoencoder-for-context#ran","syntology_url":"https://syntology.ai/paper/2307.06945","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2307.06945"}},"official":{"repos":["getao/icae"],"state":"official (archive's flag): 6 ran","n_ran":6,"n_constructed":0,"n_ran_no_instrument_failure":3,"n_unverified":0,"ran_from_kinds":["official"]}}}],"record_sha256":"303edb43aef9b479c60b4beb5de1ac04649b6711232a3b9808b746dc87a6188a","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}