{"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/abstractive-text-summarization/papers/ran/1","list_of":"/task/abstractive-text-summarization","task":"Abstractive Text Summarization","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":1,"pages_in_order":1,"rows_per_page":100,"rows":[1,77],"of":77,"counts":{"archive_papers_tagged":846,"with_a_code_link":362,"where_syntology_ran_a_sample":77,"not_listed_spam_title":0,"listed":846,"listed_where_code_ran":77,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":65,"every_run_a_failure_of_syntologys_instrument":12,"listed_with_a_run_with_no_instrument_failure":65,"listed_every_run_a_failure_of_syntologys_instrument":12,"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/abstractive-text-summarization/papers/ran/1","prev":null,"next":null,"papers":[{"url":"/paper/personalsum-a-user-subjective-guided","slug":"personalsum-a-user-subjective-guided","title":"PersonalSum: A User-Subjective Guided Personalized Summarization Dataset for Large Language Models","date":"2024-10-04","arxiv_id":"2410.03905","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/personalsum-a-user-subjective-guided#ran","syntology_url":"https://syntology.ai/paper/2410.03905","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2410.03905"}},"official":{"repos":["smartmediaai/personalsum"],"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/model-based-preference-optimization-in","slug":"model-based-preference-optimization-in","title":"Model-based Preference Optimization in Abstractive Summarization without Human Feedback","date":"2024-09-27","arxiv_id":"2409.18618","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":4,"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/model-based-preference-optimization-in#ran","syntology_url":"https://syntology.ai/paper/2409.18618","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2409.18618"}},"official":{"repos":["cjaep/MPO"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":3,"ran_from_kinds":["official"]}}},{"url":"/paper/rst-lora-a-discourse-aware-low-rank","slug":"rst-lora-a-discourse-aware-low-rank","title":"RST-LoRA: A Discourse-Aware Low-Rank Adaptation for Long Document Abstractive Summarization","date":"2024-05-01","arxiv_id":"2405.00657","repositories_listed":0,"syntology":{"n":7,"n_ran":6,"n_constructed":5,"n_ran_checked":5,"n_instrument":1,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":5,"n_pointer_only":7,"phrase":"6 ran (of which 5 constructed an object rather than computing a result; 5 with no instrument failure: 0 honoured, 0 violated, 5 with no contract checked; 1 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/rst-lora-a-discourse-aware-low-rank#ran","syntology_url":"https://syntology.ai/paper/2405.00657","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2405.00657"}},"official":null}},{"url":"/paper/fizz-factual-inconsistency-detection-by-zoom","slug":"fizz-factual-inconsistency-detection-by-zoom","title":"FIZZ: Factual Inconsistency Detection by Zoom-in Summary and Zoom-out Document","date":"2024-04-17","arxiv_id":"2404.11184","repositories_listed":1,"syntology":{"n":3,"n_ran":3,"n_constructed":1,"n_ran_checked":1,"n_instrument":2,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":1,"n_pointer_only":0,"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) · 0 unverified","sample_list":"/paper/fizz-factual-inconsistency-detection-by-zoom#ran","syntology_url":"https://syntology.ai/paper/2404.11184","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2404.11184"}},"official":{"repos":["plm3332/fizz"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":1,"n_ran_no_instrument_failure":1,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/kcts-knowledge-constrained-tree-search","slug":"kcts-knowledge-constrained-tree-search","title":"KCTS: Knowledge-Constrained Tree Search Decoding with Token-Level Hallucination Detection","date":"2023-10-13","arxiv_id":"2310.09044","repositories_listed":1,"syntology":{"n":5,"n_ran":3,"n_constructed":0,"n_ran_checked":2,"n_instrument":1,"n_unverified":2,"n_honours":1,"n_violates":0,"n_no_contract":1,"n_pointer_only":5,"phrase":"3 ran (of which 0 constructed an object rather than computing a result; 2 with no instrument failure: 1 honoured, 0 violated, 1 with no contract checked; 1 where Syntology's instrument failed) · 2 unverified","sample_list":"/paper/kcts-knowledge-constrained-tree-search#ran","syntology_url":"https://syntology.ai/paper/2310.09044","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2310.09044"}},"official":{"repos":["hkust-knowcomp/knowledge-constrained-decoding"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":2,"n_unverified":2,"ran_from_kinds":["official"]}}},{"url":"/paper/improving-summarization-with-human-edits","slug":"improving-summarization-with-human-edits","title":"Improving Summarization with Human Edits","date":"2023-10-09","arxiv_id":"2310.05857","repositories_listed":2,"syntology":{"n":6,"n_ran":3,"n_constructed":1,"n_ran_checked":3,"n_instrument":0,"n_unverified":3,"n_honours":0,"n_violates":0,"n_no_contract":3,"n_pointer_only":6,"phrase":"3 ran (of which 1 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/improving-summarization-with-human-edits#ran","syntology_url":"https://syntology.ai/paper/2310.05857","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2310.05857"}},"official":{"repos":["saiprabhakar/summarization_dpo_salt","seasonyao/learnfromhumanedit"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":1,"n_ran_no_instrument_failure":3,"n_unverified":3,"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/open-domain-text-evaluation-via-meta","slug":"open-domain-text-evaluation-via-meta","title":"Open-Domain Text Evaluation via Contrastive Distribution Methods","date":"2023-06-20","arxiv_id":"2306.11879","repositories_listed":1,"syntology":{"n":2,"n_ran":2,"n_constructed":0,"n_ran_checked":1,"n_instrument":1,"n_unverified":0,"n_honours":0,"n_violates":1,"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: 0 honoured, 1 violated, 0 with no contract checked; 1 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/open-domain-text-evaluation-via-meta#ran","syntology_url":"https://syntology.ai/paper/2306.11879","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2306.11879"}},"official":{"repos":["pluslabnlp/cdm"],"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/are-large-language-models-good-evaluators-for","slug":"are-large-language-models-good-evaluators-for","title":"Large Language Models are Not Yet Human-Level Evaluators for Abstractive Summarization","date":"2023-05-22","arxiv_id":"2305.13091","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":3,"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/are-large-language-models-good-evaluators-for#ran","syntology_url":"https://syntology.ai/paper/2305.13091","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2305.13091"}},"official":{"repos":["damo-nlp-sg/llm_summeval"],"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/balancing-lexical-and-semantic-quality-in","slug":"balancing-lexical-and-semantic-quality-in","title":"Balancing Lexical and Semantic Quality in Abstractive Summarization","date":"2023-05-17","arxiv_id":"2305.09898","repositories_listed":1,"syntology":{"n":1,"n_ran":1,"n_constructed":1,"n_ran_checked":1,"n_instrument":0,"n_unverified":0,"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) · 0 unverified; the one sample that ran constructed an object rather than computing a result","sample_list":"/paper/balancing-lexical-and-semantic-quality-in#ran","syntology_url":"https://syntology.ai/paper/2305.09898","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2305.09898"}},"official":{"repos":["jeewoo1025/balsum"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":1,"n_ran_no_instrument_failure":1,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/the-interpreter-understands-your-meaning-end","slug":"the-interpreter-understands-your-meaning-end","title":"The Interpreter Understands Your Meaning: End-to-end Spoken Language Understanding Aided by Speech Translation","date":"2023-05-16","arxiv_id":"2305.09652","repositories_listed":1,"syntology":{"n":11,"n_ran":10,"n_constructed":0,"n_ran_checked":10,"n_instrument":0,"n_unverified":1,"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) · 1 unverified","sample_list":"/paper/the-interpreter-understands-your-meaning-end#ran","syntology_url":"https://syntology.ai/paper/2305.09652","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2305.09652"}},"official":{"repos":["idiap/translation-aided-slu"],"state":"official (archive's flag): 10 ran","n_ran":10,"n_constructed":0,"n_ran_no_instrument_failure":10,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/lift-yourself-up-retrieval-augmented-text","slug":"lift-yourself-up-retrieval-augmented-text","title":"Lift Yourself Up: Retrieval-augmented Text Generation with Self Memory","date":"2023-05-03","arxiv_id":"2305.02437","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/lift-yourself-up-retrieval-augmented-text#ran","syntology_url":"https://syntology.ai/paper/2305.02437","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2305.02437"}},"official":{"repos":["hannibal046/selfmemory"],"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/gemini-controlling-the-sentence-level-writing","slug":"gemini-controlling-the-sentence-level-writing","title":"GEMINI: Controlling the Sentence-level Writing Style for Abstractive Text Summarization","date":"2023-04-07","arxiv_id":"2304.03548","repositories_listed":1,"syntology":{"n":7,"n_ran":6,"n_constructed":2,"n_ran_checked":4,"n_instrument":2,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":4,"n_pointer_only":6,"phrase":"6 ran (of which 2 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) · 1 unverified","sample_list":"/paper/gemini-controlling-the-sentence-level-writing#ran","syntology_url":"https://syntology.ai/paper/2304.03548","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2304.03548"}},"official":{"repos":["baoguangsheng/gemini"],"state":"official (archive's flag): 6 ran","n_ran":6,"n_constructed":2,"n_ran_no_instrument_failure":4,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/textbox-2-0-a-text-generation-library-with","slug":"textbox-2-0-a-text-generation-library-with","title":"TextBox 2.0: A Text Generation Library with Pre-trained Language Models","date":"2022-12-26","arxiv_id":"2212.13005","repositories_listed":1,"syntology":{"n":1,"n_ran":1,"n_constructed":1,"n_ran_checked":1,"n_instrument":0,"n_unverified":0,"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) · 0 unverified; the one sample that ran constructed an object rather than computing a result","sample_list":"/paper/textbox-2-0-a-text-generation-library-with#ran","syntology_url":"https://syntology.ai/paper/2212.13005","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2212.13005"}},"official":{"repos":["RUCAIBox/TextBox"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":1,"n_ran_no_instrument_failure":1,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/summarizing-community-based-question-answer","slug":"summarizing-community-based-question-answer","title":"Summarizing Community-based Question-Answer Pairs","date":"2022-11-17","arxiv_id":"2211.09892","repositories_listed":0,"syntology":{"n":8,"n_ran":7,"n_constructed":0,"n_ran_checked":6,"n_instrument":1,"n_unverified":1,"n_honours":0,"n_violates":1,"n_no_contract":5,"n_pointer_only":2,"phrase":"7 ran (of which 0 constructed an object rather than computing a result; 6 with no instrument failure: 0 honoured, 1 violated, 5 with no contract checked; 1 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/summarizing-community-based-question-answer#ran","syntology_url":"https://syntology.ai/paper/2211.09892","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2211.09892"}},"official":null}},{"url":"/paper/mutual-information-alleviates-hallucinations","slug":"mutual-information-alleviates-hallucinations","title":"Mutual Information Alleviates Hallucinations in Abstractive Summarization","date":"2022-10-24","arxiv_id":"2210.13210","repositories_listed":3,"syntology":{"n":12,"n_ran":10,"n_constructed":0,"n_ran_checked":9,"n_instrument":1,"n_unverified":2,"n_honours":0,"n_violates":0,"n_no_contract":9,"n_pointer_only":1,"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) · 2 unverified","sample_list":"/paper/mutual-information-alleviates-hallucinations#ran","syntology_url":"https://syntology.ai/paper/2210.13210","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2210.13210"}},"official":{"repos":["vanderpoelliam/cpmi"],"state":"official (archive's flag): 8 ran","n_ran":8,"n_constructed":0,"n_ran_no_instrument_failure":8,"n_unverified":0,"ran_from_kinds":["listed","official"]}}},{"url":"/paper/towards-summary-candidates-fusion","slug":"towards-summary-candidates-fusion","title":"Towards Summary Candidates Fusion","date":"2022-10-17","arxiv_id":"2210.08779","repositories_listed":1,"syntology":{"n":1,"n_ran":1,"n_constructed":1,"n_ran_checked":1,"n_instrument":0,"n_unverified":0,"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) · 0 unverified; the one sample that ran constructed an object rather than computing a result","sample_list":"/paper/towards-summary-candidates-fusion#ran","syntology_url":"https://syntology.ai/paper/2210.08779","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2210.08779"}},"official":{"repos":["ntunlp/summafusion"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":1,"n_ran_no_instrument_failure":1,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/summarization-programs-interpretable","slug":"summarization-programs-interpretable","title":"Summarization Programs: Interpretable Abstractive Summarization with Neural Modular Trees","date":"2022-09-21","arxiv_id":"2209.10492","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":0,"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/summarization-programs-interpretable#ran","syntology_url":"https://syntology.ai/paper/2209.10492","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2209.10492"}},"official":{"repos":["swarnahub/summarizationprograms"],"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/arglegalsumm-improving-abstractive","slug":"arglegalsumm-improving-abstractive","title":"ArgLegalSumm: Improving Abstractive Summarization of Legal Documents with Argument Mining","date":"2022-09-04","arxiv_id":"2209.01650","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":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/arglegalsumm-improving-abstractive#ran","syntology_url":"https://syntology.ai/paper/2209.01650","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2209.01650"}},"official":{"repos":["engsalem/arglegalsumm"],"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/meta-learning-the-difference-preparing-large","slug":"meta-learning-the-difference-preparing-large","title":"Meta-Learning the Difference: Preparing Large Language Models for Efficient Adaptation","date":"2022-07-07","arxiv_id":"2207.03509","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":0,"n_no_contract":5,"n_pointer_only":0,"phrase":"6 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; 1 where Syntology's instrument failed) · 2 unverified","sample_list":"/paper/meta-learning-the-difference-preparing-large#ran","syntology_url":"https://syntology.ai/paper/2207.03509","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2207.03509"}},"official":{"repos":["amazon-research/meta-learning-the-difference"],"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/brio-bringing-order-to-abstractive","slug":"brio-bringing-order-to-abstractive","title":"BRIO: Bringing Order to Abstractive Summarization","date":"2022-03-31","arxiv_id":"2203.16804","repositories_listed":3,"syntology":{"n":10,"n_ran":7,"n_constructed":0,"n_ran_checked":7,"n_instrument":0,"n_unverified":3,"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) · 3 unverified","sample_list":"/paper/brio-bringing-order-to-abstractive#ran","syntology_url":"https://syntology.ai/paper/2203.16804","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2203.16804"}},"official":{"repos":["yixinl7/brio"],"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/lossless-speedup-of-autoregressive","slug":"lossless-speedup-of-autoregressive","title":"Speculative Decoding: Exploiting Speculative Execution for Accelerating Seq2seq Generation","date":"2022-03-30","arxiv_id":"2203.16487","repositories_listed":2,"syntology":{"n":5,"n_ran":5,"n_constructed":0,"n_ran_checked":2,"n_instrument":3,"n_unverified":0,"n_honours":0,"n_violates":2,"n_no_contract":0,"n_pointer_only":3,"phrase":"5 ran (of which 0 constructed an object rather than computing a result; 2 with no instrument failure: 0 honoured, 2 violated, 0 with no contract checked; 3 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/lossless-speedup-of-autoregressive#ran","syntology_url":"https://syntology.ai/paper/2203.16487","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2203.16487"}},"official":{"repos":["hemingkx/gad","hemingkx/specdec"],"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":["community","official","unlocated"]}}},{"url":"/paper/ode-transformer-an-ordinary-differential-2","slug":"ode-transformer-an-ordinary-differential-2","title":"ODE Transformer: An Ordinary Differential Equation-Inspired Model for Sequence Generation","date":"2022-03-17","arxiv_id":"2203.09176","repositories_listed":1,"syntology":{"n":3,"n_ran":3,"n_constructed":3,"n_ran_checked":2,"n_instrument":1,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":2,"n_pointer_only":3,"phrase":"3 ran (of which 3 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) · 0 unverified; every one of the 3 samples that ran constructed an object rather than computing a result","sample_list":"/paper/ode-transformer-an-ordinary-differential-2#ran","syntology_url":"https://syntology.ai/paper/2203.09176","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2203.09176"}},"official":{"repos":["libeineu/ode-transformer"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":3,"n_ran_no_instrument_failure":2,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/summareranker-a-multi-task-mixture-of-experts-1","slug":"summareranker-a-multi-task-mixture-of-experts-1","title":"SummaReranker: A Multi-Task Mixture-of-Experts Re-ranking Framework for Abstractive Summarization","date":"2022-03-13","arxiv_id":"2203.06569","repositories_listed":1,"syntology":{"n":3,"n_ran":2,"n_constructed":2,"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 2 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; every one of the 2 samples that ran constructed an object rather than computing a result","sample_list":"/paper/summareranker-a-multi-task-mixture-of-experts-1#ran","syntology_url":"https://syntology.ai/paper/2203.06569","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2203.06569"}},"official":{"repos":["ntunlp/summareranker"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":2,"n_ran_no_instrument_failure":2,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/typical-decoding-for-natural-language","slug":"typical-decoding-for-natural-language","title":"Locally Typical Sampling","date":"2022-02-01","arxiv_id":"2202.00666","repositories_listed":3,"syntology":{"n":25,"n_ran":19,"n_constructed":0,"n_ran_checked":18,"n_instrument":1,"n_unverified":6,"n_honours":0,"n_violates":0,"n_no_contract":18,"n_pointer_only":15,"phrase":"19 ran (of which 0 constructed an object rather than computing a result; 18 with no instrument failure: 0 honoured, 0 violated, 18 with no contract checked; 1 where Syntology's instrument failed) · 6 unverified","sample_list":"/paper/typical-decoding-for-natural-language#ran","syntology_url":"https://syntology.ai/paper/2202.00666","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2202.00666"}},"official":{"repos":["cimeister/typical-sampling"],"state":"official (archive's flag): 10 ran","n_ran":10,"n_constructed":0,"n_ran_no_instrument_failure":9,"n_unverified":5,"ran_from_kinds":["listed","official"]}}},{"url":"/paper/longt5-efficient-text-to-text-transformer-for","slug":"longt5-efficient-text-to-text-transformer-for","title":"LongT5: Efficient Text-To-Text Transformer for Long Sequences","date":"2021-12-15","arxiv_id":"2112.07916","repositories_listed":4,"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/longt5-efficient-text-to-text-transformer-for#ran","syntology_url":"https://syntology.ai/paper/2112.07916","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2112.07916"}},"official":{"repos":["google-research/longt5"],"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/controlling-conditional-language-models-with","slug":"controlling-conditional-language-models-with","title":"Controlling Conditional Language Models without Catastrophic Forgetting","date":"2021-12-01","arxiv_id":"2112.00791","repositories_listed":2,"syntology":{"n":8,"n_ran":7,"n_constructed":1,"n_ran_checked":5,"n_instrument":2,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":5,"n_pointer_only":4,"phrase":"7 ran (of which 1 constructed an object rather than computing a result; 5 with no instrument failure: 0 honoured, 0 violated, 5 with no contract checked; 2 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/controlling-conditional-language-models-with#ran","syntology_url":"https://syntology.ai/paper/2112.00791","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2112.00791"}},"official":{"repos":["naver/gdc"],"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":["listed","official"]}}},{"url":"/paper/primer-pyramid-based-masked-sentence-pre","slug":"primer-pyramid-based-masked-sentence-pre","title":"PRIMERA: Pyramid-based Masked Sentence Pre-training for Multi-document Summarization","date":"2021-10-16","arxiv_id":"2110.08499","repositories_listed":3,"syntology":{"n":7,"n_ran":7,"n_constructed":0,"n_ran_checked":4,"n_instrument":3,"n_unverified":0,"n_honours":1,"n_violates":0,"n_no_contract":3,"n_pointer_only":0,"phrase":"7 ran (of which 0 constructed an object rather than computing a result; 4 with no instrument failure: 1 honoured, 0 violated, 3 with no contract checked; 3 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/primer-pyramid-based-masked-sentence-pre#ran","syntology_url":"https://syntology.ai/paper/2110.08499","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2110.08499"}},"official":{"repos":["allenai/primer"],"state":"official (archive's flag): 4 ran","n_ran":4,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":0,"ran_from_kinds":["listed","official"]}}},{"url":"/paper/towards-making-the-most-of-multilingual","slug":"towards-making-the-most-of-multilingual","title":"Towards Making the Most of Multilingual Pretraining for Zero-Shot Neural Machine Translation","date":"2021-10-16","arxiv_id":"2110.08547","repositories_listed":1,"syntology":{"n":2,"n_ran":2,"n_constructed":0,"n_ran_checked":1,"n_instrument":1,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":1,"n_pointer_only":2,"phrase":"2 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; 1 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/towards-making-the-most-of-multilingual#ran","syntology_url":"https://syntology.ai/paper/2110.08547","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2110.08547"}},"official":{"repos":["ghchen18/acl22-sixtp"],"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/hydrasum-disentangling-stylistic-features-in-1","slug":"hydrasum-disentangling-stylistic-features-in-1","title":"HydraSum: Disentangling Stylistic Features in Text Summarization using Multi-Decoder Models","date":"2021-10-08","arxiv_id":"2110.04400","repositories_listed":1,"syntology":{"n":9,"n_ran":3,"n_constructed":0,"n_ran_checked":3,"n_instrument":0,"n_unverified":6,"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) · 6 unverified","sample_list":"/paper/hydrasum-disentangling-stylistic-features-in-1#ran","syntology_url":"https://syntology.ai/paper/2110.04400","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2110.04400"}},"official":{"repos":["salesforce/hydra-sum"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":3,"n_unverified":6,"ran_from_kinds":["official"]}}},{"url":"/paper/inspecting-the-factuality-of-hallucinated","slug":"inspecting-the-factuality-of-hallucinated","title":"Hallucinated but Factual! Inspecting the Factuality of Hallucinations in Abstractive Summarization","date":"2021-08-30","arxiv_id":"2109.09784","repositories_listed":1,"syntology":{"n":2,"n_ran":2,"n_constructed":0,"n_ran_checked":0,"n_instrument":2,"n_unverified":0,"n_honours":0,"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; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 2 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/inspecting-the-factuality-of-hallucinated#ran","syntology_url":"https://syntology.ai/paper/2109.09784","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2109.09784"}},"official":{"repos":["mcao516/entfa"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/alleviating-exposure-bias-via-contrastive","slug":"alleviating-exposure-bias-via-contrastive","title":"Alleviating Exposure Bias via Contrastive Learning for Abstractive Text Summarization","date":"2021-08-26","arxiv_id":"2108.11846","repositories_listed":1,"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":2,"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/alleviating-exposure-bias-via-contrastive#ran","syntology_url":"https://syntology.ai/paper/2108.11846","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2108.11846"}},"official":{"repos":["shichaosun/conabssum"],"state":"official (archive's flag): 5 ran","n_ran":5,"n_constructed":0,"n_ran_no_instrument_failure":5,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/r-drop-regularized-dropout-for-neural","slug":"r-drop-regularized-dropout-for-neural","title":"R-Drop: Regularized Dropout for Neural Networks","date":"2021-06-28","arxiv_id":"2106.14448","repositories_listed":8,"syntology":{"n":6,"n_ran":4,"n_constructed":2,"n_ran_checked":4,"n_instrument":0,"n_unverified":2,"n_honours":0,"n_violates":0,"n_no_contract":4,"n_pointer_only":0,"phrase":"4 ran (of which 2 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/r-drop-regularized-dropout-for-neural#ran","syntology_url":"https://syntology.ai/paper/2106.14448","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2106.14448"}},"official":{"repos":["dropreg/R-Drop"],"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/xl-sum-large-scale-multilingual-abstractive","slug":"xl-sum-large-scale-multilingual-abstractive","title":"XL-Sum: Large-Scale Multilingual Abstractive Summarization for 44 Languages","date":"2021-06-25","arxiv_id":"2106.13822","repositories_listed":2,"syntology":{"n":3,"n_ran":2,"n_constructed":0,"n_ran_checked":0,"n_instrument":2,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":0,"n_pointer_only":3,"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) · 1 unverified","sample_list":"/paper/xl-sum-large-scale-multilingual-abstractive#ran","syntology_url":"https://syntology.ai/paper/2106.13822","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2106.13822"}},"official":{"repos":["csebuetnlp/xl-sum"],"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/simcls-a-simple-framework-for-contrastive","slug":"simcls-a-simple-framework-for-contrastive","title":"SimCLS: A Simple Framework for Contrastive Learning of Abstractive Summarization","date":"2021-06-03","arxiv_id":"2106.01890","repositories_listed":2,"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":1,"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/simcls-a-simple-framework-for-contrastive#ran","syntology_url":"https://syntology.ai/paper/2106.01890","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2106.01890"}},"official":{"repos":["yixinL7/SimCLS"],"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":["listed","official"]}}},{"url":"/paper/enriching-transformers-with-structured-tensor","slug":"enriching-transformers-with-structured-tensor","title":"Enriching Transformers with Structured Tensor-Product Representations for Abstractive Summarization","date":"2021-06-02","arxiv_id":"2106.01317","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":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) · 0 unverified","sample_list":"/paper/enriching-transformers-with-structured-tensor#ran","syntology_url":"https://syntology.ai/paper/2106.01317","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2106.01317"}},"official":{"repos":["jiangycTarheel/TPT-Summ"],"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/cross-lingual-abstractive-summarization-with","slug":"cross-lingual-abstractive-summarization-with","title":"Cross-Lingual Abstractive Summarization with Limited Parallel Resources","date":"2021-05-28","arxiv_id":"2105.13648","repositories_listed":1,"syntology":{"n":11,"n_ran":6,"n_constructed":4,"n_ran_checked":5,"n_instrument":1,"n_unverified":5,"n_honours":0,"n_violates":0,"n_no_contract":5,"n_pointer_only":0,"phrase":"6 ran (of which 4 constructed an object rather than computing a result; 5 with no instrument failure: 0 honoured, 0 violated, 5 with no contract checked; 1 where Syntology's instrument failed) · 5 unverified","sample_list":"/paper/cross-lingual-abstractive-summarization-with#ran","syntology_url":"https://syntology.ai/paper/2105.13648","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2105.13648"}},"official":{"repos":["WoodenWhite/MCLAS"],"state":"official (archive's flag): 6 ran","n_ran":6,"n_constructed":4,"n_ran_no_instrument_failure":5,"n_unverified":5,"ran_from_kinds":["official"]}}},{"url":"/paper/booksum-a-collection-of-datasets-for-long","slug":"booksum-a-collection-of-datasets-for-long","title":"BookSum: A Collection of Datasets for Long-form Narrative Summarization","date":"2021-05-18","arxiv_id":"2105.08209","repositories_listed":2,"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":0,"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/booksum-a-collection-of-datasets-for-long#ran","syntology_url":"https://syntology.ai/paper/2105.08209","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2105.08209"}},"official":{"repos":["salesforce/booksum"],"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/improving-factual-consistency-of-abstractive","slug":"improving-factual-consistency-of-abstractive","title":"Improving Factual Consistency of Abstractive Summarization via Question Answering","date":"2021-05-10","arxiv_id":"2105.04623","repositories_listed":1,"syntology":{"n":1,"n_ran":1,"n_constructed":0,"n_ran_checked":1,"n_instrument":0,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":1,"n_pointer_only":1,"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) · 0 unverified","sample_list":"/paper/improving-factual-consistency-of-abstractive#ran","syntology_url":"https://syntology.ai/paper/2105.04623","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2105.04623"}},"official":null}},{"url":"/paper/the-factual-inconsistency-problem-in","slug":"the-factual-inconsistency-problem-in","title":"The Factual Inconsistency Problem in Abstractive Text Summarization: A Survey","date":"2021-04-30","arxiv_id":"2104.14839","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":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) · 2 unverified","sample_list":"/paper/the-factual-inconsistency-problem-in#ran","syntology_url":"https://syntology.ai/paper/2104.14839","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2104.14839"}},"official":null}},{"url":"/paper/understanding-factuality-in-abstractive","slug":"understanding-factuality-in-abstractive","title":"Understanding Factuality in Abstractive Summarization with FRANK: A Benchmark for Factuality Metrics","date":"2021-04-27","arxiv_id":"2104.13346","repositories_listed":2,"syntology":{"n":3,"n_ran":3,"n_constructed":0,"n_ran_checked":2,"n_instrument":1,"n_unverified":0,"n_honours":2,"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; 2 with no instrument failure: 2 honoured, 0 violated, 0 with no contract checked; 1 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/understanding-factuality-in-abstractive#ran","syntology_url":"https://syntology.ai/paper/2104.13346","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2104.13346"}},"official":{"repos":["artidoro/frank"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":2,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/q-2-evaluating-factual-consistency-in","slug":"q-2-evaluating-factual-consistency-in","title":"$Q^{2}$: Evaluating Factual Consistency in Knowledge-Grounded Dialogues via Question Generation and Question Answering","date":"2021-04-16","arxiv_id":"2104.08202","repositories_listed":1,"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":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) · 1 unverified","sample_list":"/paper/q-2-evaluating-factual-consistency-in#ran","syntology_url":"https://syntology.ai/paper/2104.08202","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2104.08202"}},"official":null}},{"url":"/paper/summvis-interactive-visual-analysis-of-models","slug":"summvis-interactive-visual-analysis-of-models","title":"SummVis: Interactive Visual Analysis of Models, Data, and Evaluation for Text Summarization","date":"2021-04-15","arxiv_id":"2104.07605","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":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/summvis-interactive-visual-analysis-of-models#ran","syntology_url":"https://syntology.ai/paper/2104.07605","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2104.07605"}},"official":{"repos":["robustness-gym/summvis"],"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/annotating-and-modeling-fine-grained","slug":"annotating-and-modeling-fine-grained","title":"Annotating and Modeling Fine-grained Factuality in Summarization","date":"2021-04-09","arxiv_id":"2104.04302","repositories_listed":3,"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":3,"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/annotating-and-modeling-fine-grained#ran","syntology_url":"https://syntology.ai/paper/2104.04302","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2104.04302"}},"official":{"repos":["tagoyal/factuality-datasets"],"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/mask-attention-networks-rethinking-and","slug":"mask-attention-networks-rethinking-and","title":"Mask Attention Networks: Rethinking and Strengthen Transformer","date":"2021-03-25","arxiv_id":"2103.13597","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/mask-attention-networks-rethinking-and#ran","syntology_url":"https://syntology.ai/paper/2103.13597","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2103.13597"}},"official":null}},{"url":"/paper/all-nlp-tasks-are-generation-tasks-a-general","slug":"all-nlp-tasks-are-generation-tasks-a-general","title":"GLM: General Language Model Pretraining with Autoregressive Blank Infilling","date":"2021-03-18","arxiv_id":"2103.10360","repositories_listed":8,"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/all-nlp-tasks-are-generation-tasks-a-general#ran","syntology_url":"https://syntology.ai/paper/2103.10360","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2103.10360"}},"official":{"repos":["THUDM/GLM"],"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/iot-instance-wise-layer-reordering-for-1","slug":"iot-instance-wise-layer-reordering-for-1","title":"IOT: Instance-wise Layer Reordering for Transformer Structures","date":"2021-03-05","arxiv_id":"2103.03457","repositories_listed":1,"syntology":{"n":5,"n_ran":3,"n_constructed":3,"n_ran_checked":1,"n_instrument":2,"n_unverified":2,"n_honours":0,"n_violates":0,"n_no_contract":1,"n_pointer_only":5,"phrase":"3 ran (of which 3 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) · 2 unverified; every one of the 3 samples that ran constructed an object rather than computing a result","sample_list":"/paper/iot-instance-wise-layer-reordering-for-1#ran","syntology_url":"https://syntology.ai/paper/2103.03457","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2103.03457"}},"official":{"repos":["instance-wise-ordered-transformer/IOT"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":3,"n_ran_no_instrument_failure":1,"n_unverified":2,"ran_from_kinds":["official"]}}},{"url":"/paper/debatesum-a-large-scale-argument-mining-and","slug":"debatesum-a-large-scale-argument-mining-and","title":"DebateSum: A large-scale argument mining and summarization dataset","date":"2020-11-14","arxiv_id":"2011.07251","repositories_listed":3,"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/debatesum-a-large-scale-argument-mining-and#ran","syntology_url":"https://syntology.ai/paper/2011.07251","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2011.07251"}},"official":{"repos":["Hellisotherpeople/DebateSum","Hellisotherpeople/debate2vec","arvind-balaji/debate-cards"],"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/gsum-a-general-framework-for-guided-neural","slug":"gsum-a-general-framework-for-guided-neural","title":"GSum: A General Framework for Guided Neural Abstractive Summarization","date":"2020-10-15","arxiv_id":"2010.08014","repositories_listed":1,"syntology":{"n":3,"n_ran":3,"n_constructed":2,"n_ran_checked":1,"n_instrument":2,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":1,"n_pointer_only":2,"phrase":"3 ran (of which 2 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) · 0 unverified","sample_list":"/paper/gsum-a-general-framework-for-guided-neural#ran","syntology_url":"https://syntology.ai/paper/2010.08014","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2010.08014"}},"official":{"repos":["neulab/guided_summarization"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":2,"n_ran_no_instrument_failure":1,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/q-learning-with-language-model-for-edit-based","slug":"q-learning-with-language-model-for-edit-based","title":"Q-learning with Language Model for Edit-based Unsupervised Summarization","date":"2020-10-09","arxiv_id":"2010.04379","repositories_listed":1,"syntology":{"n":2,"n_ran":2,"n_constructed":0,"n_ran_checked":0,"n_instrument":2,"n_unverified":0,"n_honours":0,"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; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 2 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/q-learning-with-language-model-for-edit-based#ran","syntology_url":"https://syntology.ai/paper/2010.04379","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2010.04379"}},"official":{"repos":["kohilin/ealm"],"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":["found_in_text"]}}},{"url":"/paper/on-faithfulness-and-factuality-in-abstractive","slug":"on-faithfulness-and-factuality-in-abstractive","title":"On Faithfulness and Factuality in Abstractive Summarization","date":"2020-05-02","arxiv_id":"2005.00661","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":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/on-faithfulness-and-factuality-in-abstractive#ran","syntology_url":"https://syntology.ai/paper/2005.00661","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2005.00661"}},"official":{"repos":["google-research-datasets/xsum_hallucination_annotations"],"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":["found_in_text"]}}},{"url":"/paper/synthesizer-rethinking-self-attention-in","slug":"synthesizer-rethinking-self-attention-in","title":"Synthesizer: Rethinking Self-Attention in Transformer Models","date":"2020-05-02","arxiv_id":"2005.00743","repositories_listed":1,"syntology":{"n":1,"n_ran":1,"n_constructed":1,"n_ran_checked":1,"n_instrument":0,"n_unverified":0,"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) · 0 unverified; the one sample that ran constructed an object rather than computing a result","sample_list":"/paper/synthesizer-rethinking-self-attention-in#ran","syntology_url":"https://syntology.ai/paper/2005.00743","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2005.00743"}},"official":null}},{"url":"/paper/tldr-extreme-summarization-of-scientific","slug":"tldr-extreme-summarization-of-scientific","title":"TLDR: Extreme Summarization of Scientific Documents","date":"2020-04-30","arxiv_id":"2004.15011","repositories_listed":4,"syntology":{"n":19,"n_ran":17,"n_constructed":1,"n_ran_checked":10,"n_instrument":7,"n_unverified":2,"n_honours":4,"n_violates":0,"n_no_contract":6,"n_pointer_only":4,"phrase":"17 ran (of which 1 constructed an object rather than computing a result; 10 with no instrument failure: 4 honoured, 0 violated, 6 with no contract checked; 7 where Syntology's instrument failed) · 2 unverified","sample_list":"/paper/tldr-extreme-summarization-of-scientific#ran","syntology_url":"https://syntology.ai/paper/2004.15011","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2004.15011"}},"official":{"repos":["allenai/scitldr"],"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":["listed","official"]}}},{"url":"/paper/abstractive-text-summarization-based-on","slug":"abstractive-text-summarization-based-on","title":"Abstractive Text Summarization based on Language Model Conditioning and Locality Modeling","date":"2020-03-29","arxiv_id":"2003.13027","repositories_listed":1,"syntology":{"n":2,"n_ran":2,"n_constructed":0,"n_ran_checked":2,"n_instrument":0,"n_unverified":0,"n_honours":1,"n_violates":0,"n_no_contract":1,"n_pointer_only":0,"phrase":"2 ran (of which 0 constructed an object rather than computing a result; 2 with no instrument failure: 1 honoured, 0 violated, 1 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/abstractive-text-summarization-based-on#ran","syntology_url":"https://syntology.ai/paper/2003.13027","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2003.13027"}},"official":{"repos":["axenov/BERT-Summ-OpenNMT"],"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/bert-fine-tuning-for-arabic-text","slug":"bert-fine-tuning-for-arabic-text","title":"BERT Fine-tuning For Arabic Text Summarization","date":"2020-03-29","arxiv_id":"2004.14135","repositories_listed":1,"syntology":{"n":8,"n_ran":8,"n_constructed":0,"n_ran_checked":8,"n_instrument":0,"n_unverified":0,"n_honours":0,"n_violates":1,"n_no_contract":7,"n_pointer_only":5,"phrase":"8 ran (of which 0 constructed an object rather than computing a result; 8 with no instrument failure: 0 honoured, 1 violated, 7 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/bert-fine-tuning-for-arabic-text#ran","syntology_url":"https://syntology.ai/paper/2004.14135","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2004.14135"}},"official":{"repos":["mukhtar-algezoli/Arabic_PreSumm"],"state":"official (archive's flag): 8 ran","n_ran":8,"n_constructed":0,"n_ran_no_instrument_failure":8,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/unilmv2-pseudo-masked-language-models-for","slug":"unilmv2-pseudo-masked-language-models-for","title":"UniLMv2: Pseudo-Masked Language Models for Unified Language Model Pre-Training","date":"2020-02-28","arxiv_id":"2002.12804","repositories_listed":3,"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/unilmv2-pseudo-masked-language-models-for#ran","syntology_url":"https://syntology.ai/paper/2002.12804","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2002.12804"}},"official":{"repos":["microsoft/unilm"],"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/pegasus-pre-training-with-extracted-gap","slug":"pegasus-pre-training-with-extracted-gap","title":"PEGASUS: Pre-training with Extracted Gap-sentences for Abstractive Summarization","date":"2019-12-18","arxiv_id":"1912.08777","repositories_listed":19,"syntology":{"n":19,"n_ran":16,"n_constructed":0,"n_ran_checked":15,"n_instrument":1,"n_unverified":3,"n_honours":0,"n_violates":0,"n_no_contract":15,"n_pointer_only":0,"phrase":"16 ran (of which 0 constructed an object rather than computing a result; 15 with no instrument failure: 0 honoured, 0 violated, 15 with no contract checked; 1 where Syntology's instrument failed) · 3 unverified","sample_list":"/paper/pegasus-pre-training-with-extracted-gap#ran","syntology_url":"https://syntology.ai/paper/1912.08777","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1912.08777"}},"official":{"repos":["google-research/pegasus"],"state":"official (archive's flag): 7 ran","n_ran":7,"n_constructed":0,"n_ran_no_instrument_failure":7,"n_unverified":2,"ran_from_kinds":["listed","official"]}}},{"url":"/paper/bart-denoising-sequence-to-sequence-pre","slug":"bart-denoising-sequence-to-sequence-pre","title":"BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehension","date":"2019-10-29","arxiv_id":"1910.13461","repositories_listed":47,"syntology":{"n":53,"n_ran":40,"n_constructed":7,"n_ran_checked":31,"n_instrument":9,"n_unverified":13,"n_honours":1,"n_violates":1,"n_no_contract":29,"n_pointer_only":13,"phrase":"40 ran (of which 7 constructed an object rather than computing a result; 31 with no instrument failure: 1 honoured, 1 violated, 29 with no contract checked; 9 where Syntology's instrument failed) · 13 unverified","sample_list":"/paper/bart-denoising-sequence-to-sequence-pre#ran","syntology_url":"https://syntology.ai/paper/1910.13461","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1910.13461"}},"official":null}},{"url":"/paper/evaluating-the-factual-consistency-of","slug":"evaluating-the-factual-consistency-of","title":"Evaluating the Factual Consistency of Abstractive Text Summarization","date":"2019-10-28","arxiv_id":"1910.12840","repositories_listed":4,"syntology":{"n":3,"n_ran":3,"n_constructed":0,"n_ran_checked":1,"n_instrument":2,"n_unverified":0,"n_honours":1,"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; 1 with no instrument failure: 1 honoured, 0 violated, 0 with no contract checked; 2 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/evaluating-the-factual-consistency-of#ran","syntology_url":"https://syntology.ai/paper/1910.12840","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1910.12840"}},"official":{"repos":["yuhui-zh15/FactCCX"],"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":["listed","official"]}}},{"url":"/paper/on-extractive-and-abstractive-neural-document","slug":"on-extractive-and-abstractive-neural-document","title":"On Extractive and Abstractive Neural Document Summarization with Transformer Language Models","date":"2019-09-07","arxiv_id":"1909.03186","repositories_listed":1,"syntology":{"n":6,"n_ran":1,"n_constructed":0,"n_ran_checked":1,"n_instrument":0,"n_unverified":5,"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) · 5 unverified","sample_list":"/paper/on-extractive-and-abstractive-neural-document#ran","syntology_url":"https://syntology.ai/paper/1909.03186","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1909.03186"}},"official":null}},{"url":"/paper/answers-unite-unsupervised-metrics-for","slug":"answers-unite-unsupervised-metrics-for","title":"Answers Unite! Unsupervised Metrics for Reinforced Summarization Models","date":"2019-09-04","arxiv_id":"1909.01610","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":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/answers-unite-unsupervised-metrics-for#ran","syntology_url":"https://syntology.ai/paper/1909.01610","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1909.01610"}},"official":{"repos":["recitalAI/summa-qa"],"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/encode-tag-realize-high-precision-text","slug":"encode-tag-realize-high-precision-text","title":"Encode, Tag, Realize: High-Precision Text Editing","date":"2019-09-03","arxiv_id":"1909.01187","repositories_listed":5,"syntology":{"n":11,"n_ran":8,"n_constructed":0,"n_ran_checked":7,"n_instrument":1,"n_unverified":3,"n_honours":1,"n_violates":0,"n_no_contract":6,"n_pointer_only":1,"phrase":"8 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; 1 where Syntology's instrument failed) · 3 unverified","sample_list":"/paper/encode-tag-realize-high-precision-text#ran","syntology_url":"https://syntology.ai/paper/1909.01187","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1909.01187"}},"official":{"repos":["google-research/lasertagger"],"state":"official (archive's flag): 5 ran","n_ran":5,"n_constructed":0,"n_ran_no_instrument_failure":5,"n_unverified":1,"ran_from_kinds":["listed","official"]}}},{"url":"/paper/text-summarization-with-pretrained-encoders","slug":"text-summarization-with-pretrained-encoders","title":"Text Summarization with Pretrained Encoders","date":"2019-08-22","arxiv_id":"1908.08345","repositories_listed":19,"syntology":{"n":21,"n_ran":13,"n_constructed":0,"n_ran_checked":12,"n_instrument":1,"n_unverified":8,"n_honours":0,"n_violates":1,"n_no_contract":11,"n_pointer_only":5,"phrase":"13 ran (of which 0 constructed an object rather than computing a result; 12 with no instrument failure: 0 honoured, 1 violated, 11 with no contract checked; 1 where Syntology's instrument failed) · 8 unverified","sample_list":"/paper/text-summarization-with-pretrained-encoders#ran","syntology_url":"https://syntology.ai/paper/1908.08345","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1908.08345"}},"official":{"repos":["nlpyang/PreSumm"],"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/positional-encoding-to-control-output","slug":"positional-encoding-to-control-output","title":"Positional Encoding to Control Output Sequence Length","date":"2019-04-16","arxiv_id":"1904.07418","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/positional-encoding-to-control-output#ran","syntology_url":"https://syntology.ai/paper/1904.07418","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1904.07418"}},"official":{"repos":["takase/control-length"],"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/pretraining-based-natural-language-generation","slug":"pretraining-based-natural-language-generation","title":"Pretraining-Based Natural Language Generation for Text Summarization","date":"2019-02-25","arxiv_id":"1902.09243","repositories_listed":4,"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/pretraining-based-natural-language-generation#ran","syntology_url":"https://syntology.ai/paper/1902.09243","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1902.09243"}},"official":null}},{"url":"/paper/neural-abstractive-text-summarization-with","slug":"neural-abstractive-text-summarization-with","title":"Neural Abstractive Text Summarization with Sequence-to-Sequence Models","date":"2018-12-05","arxiv_id":"1812.02303","repositories_listed":5,"syntology":{"n":2,"n_ran":1,"n_constructed":0,"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 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) · 1 unverified","sample_list":"/paper/neural-abstractive-text-summarization-with#ran","syntology_url":"https://syntology.ai/paper/1812.02303","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1812.02303"}},"official":{"repos":["tshi04/NATS"],"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/meansum-a-neural-model-for-unsupervised-multi","slug":"meansum-a-neural-model-for-unsupervised-multi","title":"MeanSum: A Neural Model for Unsupervised Multi-document Abstractive Summarization","date":"2018-10-12","arxiv_id":"1810.05739","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/meansum-a-neural-model-for-unsupervised-multi#ran","syntology_url":"https://syntology.ai/paper/1810.05739","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1810.05739"}},"official":{"repos":["sosuperic/MeanSum"],"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/learning-to-encode-text-as-human-readable","slug":"learning-to-encode-text-as-human-readable","title":"Learning to Encode Text as Human-Readable Summaries using Generative Adversarial Networks","date":"2018-10-05","arxiv_id":"1810.02851","repositories_listed":1,"syntology":{"n":2,"n_ran":2,"n_constructed":0,"n_ran_checked":1,"n_instrument":1,"n_unverified":0,"n_honours":0,"n_violates":1,"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: 0 honoured, 1 violated, 0 with no contract checked; 1 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/learning-to-encode-text-as-human-readable#ran","syntology_url":"https://syntology.ai/paper/1810.02851","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1810.02851"}},"official":null}},{"url":"/paper/bottom-up-abstractive-summarization","slug":"bottom-up-abstractive-summarization","title":"Bottom-Up Abstractive Summarization","date":"2018-08-31","arxiv_id":"1808.10792","repositories_listed":5,"syntology":{"n":6,"n_ran":5,"n_constructed":0,"n_ran_checked":0,"n_instrument":5,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":0,"n_pointer_only":0,"phrase":"5 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; 5 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/bottom-up-abstractive-summarization#ran","syntology_url":"https://syntology.ai/paper/1808.10792","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1808.10792"}},"official":{"repos":["sebastianGehrmann/bottom-up-summary"],"state":"official (archive's flag): 5 ran","n_ran":5,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/fast-abstractive-summarization-with-reinforce","slug":"fast-abstractive-summarization-with-reinforce","title":"Fast Abstractive Summarization with Reinforce-Selected Sentence Rewriting","date":"2018-05-28","arxiv_id":"1805.11080","repositories_listed":3,"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":2,"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/fast-abstractive-summarization-with-reinforce#ran","syntology_url":"https://syntology.ai/paper/1805.11080","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1805.11080"}},"official":{"repos":["ChenRocks/fast_abs_rl"],"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/deep-reinforcement-learning-for-sequence-to","slug":"deep-reinforcement-learning-for-sequence-to","title":"Deep Reinforcement Learning For Sequence to Sequence Models","date":"2018-05-24","arxiv_id":"1805.09461","repositories_listed":3,"syntology":{"n":17,"n_ran":16,"n_constructed":0,"n_ran_checked":15,"n_instrument":1,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":15,"n_pointer_only":2,"phrase":"16 ran (of which 0 constructed an object rather than computing a result; 15 with no instrument failure: 0 honoured, 0 violated, 15 with no contract checked; 1 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/deep-reinforcement-learning-for-sequence-to#ran","syntology_url":"https://syntology.ai/paper/1805.09461","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1805.09461"}},"official":{"repos":["yaserkl/RLSeq2Seq"],"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":["listed","official"]}}},{"url":"/paper/a-unified-model-for-extractive-and","slug":"a-unified-model-for-extractive-and","title":"A Unified Model for Extractive and Abstractive Summarization using Inconsistency Loss","date":"2018-05-16","arxiv_id":"1805.06266","repositories_listed":1,"syntology":{"n":7,"n_ran":3,"n_constructed":0,"n_ran_checked":2,"n_instrument":1,"n_unverified":4,"n_honours":0,"n_violates":0,"n_no_contract":2,"n_pointer_only":0,"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) · 4 unverified","sample_list":"/paper/a-unified-model-for-extractive-and#ran","syntology_url":"https://syntology.ai/paper/1805.06266","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1805.06266"}},"official":null}},{"url":"/paper/global-encoding-for-abstractive-summarization","slug":"global-encoding-for-abstractive-summarization","title":"Global Encoding for Abstractive Summarization","date":"2018-05-10","arxiv_id":"1805.03989","repositories_listed":4,"syntology":{"n":7,"n_ran":3,"n_constructed":0,"n_ran_checked":2,"n_instrument":1,"n_unverified":4,"n_honours":0,"n_violates":0,"n_no_contract":2,"n_pointer_only":0,"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) · 4 unverified","sample_list":"/paper/global-encoding-for-abstractive-summarization#ran","syntology_url":"https://syntology.ai/paper/1805.03989","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1805.03989"}},"official":{"repos":["lancopku/Global-Encoding"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":3,"ran_from_kinds":["listed","official"]}}},{"url":"/paper/a-discourse-aware-attention-model-for","slug":"a-discourse-aware-attention-model-for","title":"A Discourse-Aware Attention Model for Abstractive Summarization of Long Documents","date":"2018-04-16","arxiv_id":"1804.05685","repositories_listed":3,"syntology":{"n":14,"n_ran":7,"n_constructed":0,"n_ran_checked":6,"n_instrument":1,"n_unverified":7,"n_honours":0,"n_violates":0,"n_no_contract":6,"n_pointer_only":0,"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) · 7 unverified","sample_list":"/paper/a-discourse-aware-attention-model-for#ran","syntology_url":"https://syntology.ai/paper/1804.05685","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1804.05685"}},"official":{"repos":["acohan/long-summarization"],"state":"official (archive's flag): 6 ran","n_ran":6,"n_constructed":0,"n_ran_no_instrument_failure":5,"n_unverified":5,"ran_from_kinds":["listed","official"]}}},{"url":"/paper/attention-is-all-you-need","slug":"attention-is-all-you-need","title":"Attention Is All You Need","date":"2017-06-12","arxiv_id":"1706.03762","repositories_listed":595,"syntology":{"n":946,"n_ran":610,"n_constructed":293,"n_ran_checked":529,"n_instrument":81,"n_unverified":336,"n_honours":45,"n_violates":15,"n_no_contract":469,"n_pointer_only":451,"phrase":"610 ran (of which 293 constructed an object rather than computing a result; 529 with no instrument failure: 45 honoured, 15 violated, 469 with no contract checked; 81 where Syntology's instrument failed) · 336 unverified","sample_list":"/paper/attention-is-all-you-need#ran","syntology_url":"https://syntology.ai/paper/1706.03762","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1706.03762"}},"official":{"repos":["tensorflow/tensor2tensor"],"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":["listed","unlocated"]}}},{"url":"/paper/get-to-the-point-summarization-with-pointer","slug":"get-to-the-point-summarization-with-pointer","title":"Get To The Point: Summarization with Pointer-Generator Networks","date":"2017-04-14","arxiv_id":"1704.04368","repositories_listed":39,"syntology":{"n":64,"n_ran":30,"n_constructed":11,"n_ran_checked":25,"n_instrument":5,"n_unverified":34,"n_honours":4,"n_violates":2,"n_no_contract":19,"n_pointer_only":44,"phrase":"30 ran (of which 11 constructed an object rather than computing a result; 25 with no instrument failure: 4 honoured, 2 violated, 19 with no contract checked; 5 where Syntology's instrument failed) · 34 unverified","sample_list":"/paper/get-to-the-point-summarization-with-pointer#ran","syntology_url":"https://syntology.ai/paper/1704.04368","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1704.04368"}},"official":{"repos":["abisee/pointer-generator"],"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":["listed","unlocated"]}}},{"url":"/paper/abstractive-text-summarization-using-sequence","slug":"abstractive-text-summarization-using-sequence","title":"Abstractive Text Summarization Using Sequence-to-Sequence RNNs and Beyond","date":"2016-02-19","arxiv_id":"1602.06023","repositories_listed":4,"syntology":{"n":6,"n_ran":5,"n_constructed":0,"n_ran_checked":3,"n_instrument":2,"n_unverified":1,"n_honours":2,"n_violates":1,"n_no_contract":0,"n_pointer_only":0,"phrase":"5 ran (of which 0 constructed an object rather than computing a result; 3 with no instrument failure: 2 honoured, 1 violated, 0 with no contract checked; 2 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/abstractive-text-summarization-using-sequence#ran","syntology_url":"https://syntology.ai/paper/1602.06023","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1602.06023"}},"official":null}}],"record_sha256":"ca943caee9fca435096e7a111cb54c5b97ef096b0b764c74b6c4e88eaeee00a9","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}