{"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/question-answering/papers/ran/12","list_of":"/task/question-answering","task":"Question Answering","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":12,"pages_in_order":13,"rows_per_page":100,"rows":[1101,1200],"of":1274,"counts":{"archive_papers_tagged":10817,"with_a_code_link":4171,"where_syntology_ran_a_sample":1274,"not_listed_spam_title":0,"listed":10817,"listed_where_code_ran":1274,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":1073,"every_run_a_failure_of_syntologys_instrument":201,"listed_with_a_run_with_no_instrument_failure":1073,"listed_every_run_a_failure_of_syntologys_instrument":201,"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/question-answering/papers/ran/1","prev":"/task/question-answering/papers/ran/11","next":"/task/question-answering/papers/ran/13","papers":[{"url":"/paper/unsupervised-commonsense-question-answering","slug":"unsupervised-commonsense-question-answering","title":"Unsupervised Commonsense Question Answering with Self-Talk","date":"2020-04-11","arxiv_id":"2004.05483","repositories_listed":1,"syntology":{"n":5,"n_ran":1,"n_constructed":0,"n_ran_checked":0,"n_instrument":1,"n_unverified":4,"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) · 4 unverified","sample_list":"/paper/unsupervised-commonsense-question-answering#ran","syntology_url":"https://syntology.ai/paper/2004.05483","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2004.05483"}},"official":{"repos":["vered1986/self_talk"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":4,"ran_from_kinds":["official"]}}},{"url":"/paper/dense-passage-retrieval-for-open-domain","slug":"dense-passage-retrieval-for-open-domain","title":"Dense Passage Retrieval for Open-Domain Question Answering","date":"2020-04-10","arxiv_id":"2004.04906","repositories_listed":19,"syntology":{"n":14,"n_ran":11,"n_constructed":6,"n_ran_checked":10,"n_instrument":1,"n_unverified":3,"n_honours":0,"n_violates":0,"n_no_contract":10,"n_pointer_only":9,"phrase":"11 ran (of which 6 constructed an object rather than computing a result; 10 with no instrument failure: 0 honoured, 0 violated, 10 with no contract checked; 1 where Syntology's instrument failed) · 3 unverified","sample_list":"/paper/dense-passage-retrieval-for-open-domain#ran","syntology_url":"https://syntology.ai/paper/2004.04906","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2004.04906"}},"official":{"repos":["facebookresearch/DPR"],"state":"official: harvested, nothing ran","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":1,"ran_from_kinds":["listed"]}}},{"url":"/paper/longformer-the-long-document-transformer","slug":"longformer-the-long-document-transformer","title":"Longformer: The Long-Document Transformer","date":"2020-04-10","arxiv_id":"2004.05150","repositories_listed":22,"syntology":{"n":35,"n_ran":22,"n_constructed":4,"n_ran_checked":14,"n_instrument":8,"n_unverified":13,"n_honours":1,"n_violates":1,"n_no_contract":12,"n_pointer_only":5,"phrase":"22 ran (of which 4 constructed an object rather than computing a result; 14 with no instrument failure: 1 honoured, 1 violated, 12 with no contract checked; 8 where Syntology's instrument failed) · 13 unverified","sample_list":"/paper/longformer-the-long-document-transformer#ran","syntology_url":"https://syntology.ai/paper/2004.05150","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2004.05150"}},"official":{"repos":["allenai/longformer"],"state":"official (archive's flag): 9 ran","n_ran":9,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":2,"ran_from_kinds":["listed","official"]}}},{"url":"/paper/what-do-models-learn-from-question-answering","slug":"what-do-models-learn-from-question-answering","title":"What do Models Learn from Question Answering Datasets?","date":"2020-04-07","arxiv_id":"2004.03490","repositories_listed":2,"syntology":{"n":6,"n_ran":5,"n_constructed":0,"n_ran_checked":3,"n_instrument":2,"n_unverified":1,"n_honours":1,"n_violates":1,"n_no_contract":1,"n_pointer_only":0,"phrase":"5 ran (of which 0 constructed an object rather than computing a result; 3 with no instrument failure: 1 honoured, 1 violated, 1 with no contract checked; 2 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/what-do-models-learn-from-question-answering#ran","syntology_url":"https://syntology.ai/paper/2004.03490","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2004.03490"}},"official":{"repos":["amazon-research/qa-dataset-converter"],"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":["listed","official"]}}},{"url":"/paper/tapas-weakly-supervised-table-parsing-via-pre","slug":"tapas-weakly-supervised-table-parsing-via-pre","title":"TAPAS: Weakly Supervised Table Parsing via Pre-training","date":"2020-04-05","arxiv_id":"2004.02349","repositories_listed":8,"syntology":{"n":14,"n_ran":14,"n_constructed":0,"n_ran_checked":14,"n_instrument":0,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":14,"n_pointer_only":0,"phrase":"14 ran (of which 0 constructed an object rather than computing a result; 14 with no instrument failure: 0 honoured, 0 violated, 14 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/tapas-weakly-supervised-table-parsing-via-pre#ran","syntology_url":"https://syntology.ai/paper/2004.02349","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2004.02349"}},"official":{"repos":["google-research/tapas"],"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/electra-pre-training-text-encoders-as-1","slug":"electra-pre-training-text-encoders-as-1","title":"ELECTRA: Pre-training Text Encoders as Discriminators Rather Than Generators","date":"2020-03-23","arxiv_id":"2003.10555","repositories_listed":19,"syntology":{"n":40,"n_ran":31,"n_constructed":7,"n_ran_checked":18,"n_instrument":13,"n_unverified":9,"n_honours":2,"n_violates":2,"n_no_contract":14,"n_pointer_only":10,"phrase":"31 ran (of which 7 constructed an object rather than computing a result; 18 with no instrument failure: 2 honoured, 2 violated, 14 with no contract checked; 13 where Syntology's instrument failed) · 9 unverified","sample_list":"/paper/electra-pre-training-text-encoders-as-1#ran","syntology_url":"https://syntology.ai/paper/2003.10555","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2003.10555"}},"official":{"repos":["google-research/electra"],"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/towards-ground-truth-evaluation-of-visual","slug":"towards-ground-truth-evaluation-of-visual","title":"Ground Truth Evaluation of Neural Network Explanations with CLEVR-XAI","date":"2020-03-16","arxiv_id":"2003.07258","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":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/towards-ground-truth-evaluation-of-visual#ran","syntology_url":"https://syntology.ai/paper/2003.07258","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2003.07258"}},"official":{"repos":["ahmedmagdiosman/clevr-xai","ahmedmagdiosman/simply-clevr-dataset"],"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/counterfactual-samples-synthesizing-for","slug":"counterfactual-samples-synthesizing-for","title":"Counterfactual Samples Synthesizing for Robust Visual Question Answering","date":"2020-03-14","arxiv_id":"2003.06576","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":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/counterfactual-samples-synthesizing-for#ran","syntology_url":"https://syntology.ai/paper/2003.06576","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2003.06576"}},"official":{"repos":["yanxinzju/CSS-VQA"],"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/video2commonsense-generating-commonsense","slug":"video2commonsense-generating-commonsense","title":"Video2Commonsense: Generating Commonsense Descriptions to Enrich Video Captioning","date":"2020-03-11","arxiv_id":"2003.05162","repositories_listed":2,"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/video2commonsense-generating-commonsense#ran","syntology_url":"https://syntology.ai/paper/2003.05162","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2003.05162"}},"official":{"repos":["jacobswan1/Video2Commonsense"],"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/investigating-entity-knowledge-in-bert-with-1","slug":"investigating-entity-knowledge-in-bert-with-1","title":"Investigating Entity Knowledge in BERT with Simple Neural End-To-End Entity Linking","date":"2020-03-11","arxiv_id":"2003.05473","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/investigating-entity-knowledge-in-bert-with-1#ran","syntology_url":"https://syntology.ai/paper/2003.05473","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2003.05473"}},"official":{"repos":["samuelbroscheit/entity_knowledge_in_bert"],"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/tydi-qa-a-benchmark-for-information-seeking","slug":"tydi-qa-a-benchmark-for-information-seeking","title":"TyDi QA: A Benchmark for Information-Seeking Question Answering in Typologically Diverse Languages","date":"2020-03-10","arxiv_id":"2003.05002","repositories_listed":2,"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":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) · 0 unverified","sample_list":"/paper/tydi-qa-a-benchmark-for-information-seeking#ran","syntology_url":"https://syntology.ai/paper/2003.05002","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2003.05002"}},"official":{"repos":["google-research-datasets/tydiqa"],"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/pathvqa-30000-questions-for-medical-visual","slug":"pathvqa-30000-questions-for-medical-visual","title":"PathVQA: 30000+ Questions for Medical Visual Question Answering","date":"2020-03-07","arxiv_id":"2003.10286","repositories_listed":5,"syntology":{"n":4,"n_ran":4,"n_constructed":0,"n_ran_checked":3,"n_instrument":1,"n_unverified":0,"n_honours":1,"n_violates":2,"n_no_contract":0,"n_pointer_only":4,"phrase":"4 ran (of which 0 constructed an object rather than computing a result; 3 with no instrument failure: 1 honoured, 2 violated, 0 with no contract checked; 1 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/pathvqa-30000-questions-for-medical-visual#ran","syntology_url":"https://syntology.ai/paper/2003.10286","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2003.10286"}},"official":null}},{"url":"/paper/talking-heads-attention","slug":"talking-heads-attention","title":"Talking-Heads Attention","date":"2020-03-05","arxiv_id":"2003.02436","repositories_listed":4,"syntology":{"n":3,"n_ran":3,"n_constructed":0,"n_ran_checked":3,"n_instrument":0,"n_unverified":0,"n_honours":1,"n_violates":2,"n_no_contract":0,"n_pointer_only":2,"phrase":"3 ran (of which 0 constructed an object rather than computing a result; 3 with no instrument failure: 1 honoured, 2 violated, 0 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/talking-heads-attention#ran","syntology_url":"https://syntology.ai/paper/2003.02436","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2003.02436"}},"official":{"repos":["zygmuntz/hyperband"],"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/200302645","slug":"200302645","title":"SentenceMIM: A Latent Variable Language Model","date":"2020-02-18","arxiv_id":"2003.02645","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":1,"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/200302645#ran","syntology_url":"https://syntology.ai/paper/2003.02645","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2003.02645"}},"official":null}},{"url":"/paper/transformers-as-soft-reasoners-over-language","slug":"transformers-as-soft-reasoners-over-language","title":"Transformers as Soft Reasoners over Language","date":"2020-02-14","arxiv_id":"2002.05867","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/transformers-as-soft-reasoners-over-language#ran","syntology_url":"https://syntology.ai/paper/2002.05867","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2002.05867"}},"official":null}},{"url":"/paper/self-assttentive-associative-memory","slug":"self-assttentive-associative-memory","title":"Self-Attentive Associative Memory","date":"2020-02-10","arxiv_id":"2002.03519","repositories_listed":1,"syntology":{"n":4,"n_ran":4,"n_constructed":0,"n_ran_checked":4,"n_instrument":0,"n_unverified":0,"n_honours":1,"n_violates":0,"n_no_contract":3,"n_pointer_only":1,"phrase":"4 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; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/self-assttentive-associative-memory#ran","syntology_url":"https://syntology.ai/paper/2002.03519","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2002.03519"}},"official":{"repos":["thaihungle/SAM"],"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/realm-retrieval-augmented-language-model-pre","slug":"realm-retrieval-augmented-language-model-pre","title":"REALM: Retrieval-Augmented Language Model Pre-Training","date":"2020-02-10","arxiv_id":"2002.08909","repositories_listed":6,"syntology":{"n":4,"n_ran":4,"n_constructed":1,"n_ran_checked":3,"n_instrument":1,"n_unverified":0,"n_honours":0,"n_violates":2,"n_no_contract":1,"n_pointer_only":0,"phrase":"4 ran (of which 1 constructed an object rather than computing a result; 3 with no instrument failure: 0 honoured, 2 violated, 1 with no contract checked; 1 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/realm-retrieval-augmented-language-model-pre#ran","syntology_url":"https://syntology.ai/paper/2002.08909","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2002.08909"}},"official":{"repos":["google-research/language"],"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/k-adapter-infusing-knowledge-into-pre-trained","slug":"k-adapter-infusing-knowledge-into-pre-trained","title":"K-Adapter: Infusing Knowledge into Pre-Trained Models with Adapters","date":"2020-02-05","arxiv_id":"2002.01808","repositories_listed":2,"syntology":{"n":14,"n_ran":11,"n_constructed":0,"n_ran_checked":6,"n_instrument":5,"n_unverified":3,"n_honours":1,"n_violates":0,"n_no_contract":5,"n_pointer_only":2,"phrase":"11 ran (of which 0 constructed an object rather than computing a result; 6 with no instrument failure: 1 honoured, 0 violated, 5 with no contract checked; 5 where Syntology's instrument failed) · 3 unverified","sample_list":"/paper/k-adapter-infusing-knowledge-into-pre-trained#ran","syntology_url":"https://syntology.ai/paper/2002.01808","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2002.01808"}},"official":null}},{"url":"/paper/asking-questions-the-human-way-scalable","slug":"asking-questions-the-human-way-scalable","title":"Asking Questions the Human Way: Scalable Question-Answer Generation from Text Corpus","date":"2020-01-27","arxiv_id":"2002.00748","repositories_listed":2,"syntology":{"n":8,"n_ran":7,"n_constructed":0,"n_ran_checked":6,"n_instrument":1,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":6,"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, 0 violated, 6 with no contract checked; 1 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/asking-questions-the-human-way-scalable#ran","syntology_url":"https://syntology.ai/paper/2002.00748","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2002.00748"}},"official":{"repos":["bangliu/ACS-QG"],"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","unlocated"]}}},{"url":"/paper/reformer-the-efficient-transformer-1","slug":"reformer-the-efficient-transformer-1","title":"Reformer: The Efficient Transformer","date":"2020-01-13","arxiv_id":"2001.04451","repositories_listed":10,"syntology":{"n":8,"n_ran":6,"n_constructed":1,"n_ran_checked":1,"n_instrument":5,"n_unverified":2,"n_honours":0,"n_violates":0,"n_no_contract":1,"n_pointer_only":0,"phrase":"6 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; 5 where Syntology's instrument failed) · 2 unverified","sample_list":"/paper/reformer-the-efficient-transformer-1#ran","syntology_url":"https://syntology.ai/paper/2001.04451","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2001.04451"}},"official":{"repos":["google/trax"],"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/measuring-compositional-generalization-a-1","slug":"measuring-compositional-generalization-a-1","title":"Measuring Compositional Generalization: A Comprehensive Method on Realistic Data","date":"2019-12-20","arxiv_id":"1912.09713","repositories_listed":3,"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":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) · 0 unverified","sample_list":"/paper/measuring-compositional-generalization-a-1#ran","syntology_url":"https://syntology.ai/paper/1912.09713","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1912.09713"}},"official":{"repos":["google-research/google-research"],"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/differentiable-reasoning-on-large-knowledge","slug":"differentiable-reasoning-on-large-knowledge","title":"Differentiable Reasoning on Large Knowledge Bases and Natural Language","date":"2019-12-17","arxiv_id":"1912.10824","repositories_listed":3,"syntology":{"n":26,"n_ran":15,"n_constructed":0,"n_ran_checked":15,"n_instrument":0,"n_unverified":11,"n_honours":0,"n_violates":0,"n_no_contract":15,"n_pointer_only":0,"phrase":"15 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; 0 where Syntology's instrument failed) · 11 unverified","sample_list":"/paper/differentiable-reasoning-on-large-knowledge#ran","syntology_url":"https://syntology.ai/paper/1912.10824","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1912.10824"}},"official":{"repos":["uclnlp/gntp","uclnlp/ntp","uclnlp/ctp"],"state":"official (archive's flag): 15 ran","n_ran":15,"n_constructed":0,"n_ran_no_instrument_failure":15,"n_unverified":11,"ran_from_kinds":["official"]}}},{"url":"/paper/automatic-spanish-translation-of-the-squad","slug":"automatic-spanish-translation-of-the-squad","title":"Automatic Spanish Translation of the SQuAD Dataset for Multilingual Question Answering","date":"2019-12-11","arxiv_id":"1912.05200","repositories_listed":3,"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/automatic-spanish-translation-of-the-squad#ran","syntology_url":"https://syntology.ai/paper/1912.05200","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1912.05200"}},"official":{"repos":["ccasimiro88/TranslateAlignRetrieve"],"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":["listed","official"]}}},{"url":"/paper/12-in-1-multi-task-vision-and-language","slug":"12-in-1-multi-task-vision-and-language","title":"12-in-1: Multi-Task Vision and Language Representation Learning","date":"2019-12-05","arxiv_id":"1912.02315","repositories_listed":5,"syntology":{"n":20,"n_ran":15,"n_constructed":0,"n_ran_checked":13,"n_instrument":2,"n_unverified":5,"n_honours":1,"n_violates":0,"n_no_contract":12,"n_pointer_only":20,"phrase":"15 ran (of which 0 constructed an object rather than computing a result; 13 with no instrument failure: 1 honoured, 0 violated, 12 with no contract checked; 2 where Syntology's instrument failed) · 5 unverified","sample_list":"/paper/12-in-1-multi-task-vision-and-language#ran","syntology_url":"https://syntology.ai/paper/1912.02315","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1912.02315"}},"official":{"repos":["facebookresearch/vilbert-multi-task"],"state":"official (archive's flag): 11 ran","n_ran":11,"n_constructed":0,"n_ran_no_instrument_failure":9,"n_unverified":3,"ran_from_kinds":["listed","official"]}}},{"url":"/paper/learning-to-retrieve-reasoning-paths-over-1","slug":"learning-to-retrieve-reasoning-paths-over-1","title":"Learning to Retrieve Reasoning Paths over Wikipedia Graph for Question Answering","date":"2019-11-24","arxiv_id":"1911.10470","repositories_listed":2,"syntology":{"n":6,"n_ran":6,"n_constructed":0,"n_ran_checked":5,"n_instrument":1,"n_unverified":0,"n_honours":1,"n_violates":1,"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: 1 honoured, 1 violated, 3 with no contract checked; 1 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/learning-to-retrieve-reasoning-paths-over-1#ran","syntology_url":"https://syntology.ai/paper/1911.10470","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1911.10470"}},"official":{"repos":["AkariAsai/learning_to_retrieve_reasoning_paths"],"state":"official (archive's flag): 6 ran","n_ran":6,"n_constructed":0,"n_ran_no_instrument_failure":5,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/inductive-relation-prediction-on-knowledge","slug":"inductive-relation-prediction-on-knowledge","title":"Inductive Relation Prediction by Subgraph Reasoning","date":"2019-11-16","arxiv_id":"1911.06962","repositories_listed":10,"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/inductive-relation-prediction-on-knowledge#ran","syntology_url":"https://syntology.ai/paper/1911.06962","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1911.06962"}},"official":{"repos":["kkteru/grail"],"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/knowledge-guided-text-retrieval-and-reading","slug":"knowledge-guided-text-retrieval-and-reading","title":"Knowledge Guided Text Retrieval and Reading for Open Domain Question Answering","date":"2019-11-10","arxiv_id":"1911.03868","repositories_listed":7,"syntology":{"n":6,"n_ran":6,"n_constructed":0,"n_ran_checked":2,"n_instrument":4,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":2,"n_pointer_only":4,"phrase":"6 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; 4 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/knowledge-guided-text-retrieval-and-reading#ran","syntology_url":"https://syntology.ai/paper/1911.03868","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1911.03868"}},"official":null}},{"url":"/paper/hierarchical-graph-network-for-multi-hop","slug":"hierarchical-graph-network-for-multi-hop","title":"Hierarchical Graph Network for Multi-hop Question Answering","date":"2019-11-09","arxiv_id":"1911.03631","repositories_listed":1,"syntology":{"n":6,"n_ran":4,"n_constructed":0,"n_ran_checked":4,"n_instrument":0,"n_unverified":2,"n_honours":2,"n_violates":1,"n_no_contract":1,"n_pointer_only":5,"phrase":"4 ran (of which 0 constructed an object rather than computing a result; 4 with no instrument failure: 2 honoured, 1 violated, 1 with no contract checked; 0 where Syntology's instrument failed) · 2 unverified","sample_list":"/paper/hierarchical-graph-network-for-multi-hop#ran","syntology_url":"https://syntology.ai/paper/1911.03631","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1911.03631"}},"official":{"repos":["yuwfan/HGN"],"state":"official (archive's flag): 4 ran","n_ran":4,"n_constructed":0,"n_ran_no_instrument_failure":4,"n_unverified":2,"ran_from_kinds":["official"]}}},{"url":"/paper/commongen-a-constrained-text-generation","slug":"commongen-a-constrained-text-generation","title":"CommonGen: A Constrained Text Generation Challenge for Generative Commonsense Reasoning","date":"2019-11-09","arxiv_id":"1911.03705","repositories_listed":3,"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/commongen-a-constrained-text-generation#ran","syntology_url":"https://syntology.ai/paper/1911.03705","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1911.03705"}},"official":null}},{"url":"/paper/the-techqa-dataset","slug":"the-techqa-dataset","title":"The TechQA Dataset","date":"2019-11-08","arxiv_id":"1911.02984","repositories_listed":2,"syntology":{"n":9,"n_ran":6,"n_constructed":0,"n_ran_checked":5,"n_instrument":1,"n_unverified":3,"n_honours":0,"n_violates":0,"n_no_contract":5,"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, 0 violated, 5 with no contract checked; 1 where Syntology's instrument failed) · 3 unverified","sample_list":"/paper/the-techqa-dataset#ran","syntology_url":"https://syntology.ai/paper/1911.02984","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1911.02984"}},"official":null}},{"url":"/paper/negated-lama-birds-cannot-fly","slug":"negated-lama-birds-cannot-fly","title":"Negated and Misprimed Probes for Pretrained Language Models: Birds Can Talk, But Cannot Fly","date":"2019-11-08","arxiv_id":"1911.03343","repositories_listed":2,"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/negated-lama-birds-cannot-fly#ran","syntology_url":"https://syntology.ai/paper/1911.03343","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1911.03343"}},"official":{"repos":["facebookresearch/LAMA","norakassner/LAMA_primed_negated"],"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/dice-loss-for-data-imbalanced-nlp-tasks","slug":"dice-loss-for-data-imbalanced-nlp-tasks","title":"Dice Loss for Data-imbalanced NLP Tasks","date":"2019-11-07","arxiv_id":"1911.02855","repositories_listed":4,"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/dice-loss-for-data-imbalanced-nlp-tasks#ran","syntology_url":"https://syntology.ai/paper/1911.02855","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1911.02855"}},"official":{"repos":["ShannonAI/dice_loss_for_NLP"],"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/contextualized-sparse-representation-with-1","slug":"contextualized-sparse-representation-with-1","title":"Contextualized Sparse Representations for Real-Time Open-Domain Question Answering","date":"2019-11-07","arxiv_id":"1911.02896","repositories_listed":3,"syntology":{"n":18,"n_ran":12,"n_constructed":0,"n_ran_checked":9,"n_instrument":3,"n_unverified":6,"n_honours":5,"n_violates":2,"n_no_contract":2,"n_pointer_only":7,"phrase":"12 ran (of which 0 constructed an object rather than computing a result; 9 with no instrument failure: 5 honoured, 2 violated, 2 with no contract checked; 3 where Syntology's instrument failed) · 6 unverified","sample_list":"/paper/contextualized-sparse-representation-with-1#ran","syntology_url":"https://syntology.ai/paper/1911.02896","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1911.02896"}},"official":{"repos":["jhyuklee/sparc"],"state":"official (archive's flag): 12 ran","n_ran":12,"n_constructed":0,"n_ran_no_instrument_failure":9,"n_unverified":6,"ran_from_kinds":["official"]}}},{"url":"/paper/do-multi-hop-readers-dream-of-reasoning","slug":"do-multi-hop-readers-dream-of-reasoning","title":"Do Multi-hop Readers Dream of Reasoning Chains?","date":"2019-10-31","arxiv_id":"1910.14520","repositories_listed":1,"syntology":{"n":11,"n_ran":9,"n_constructed":0,"n_ran_checked":6,"n_instrument":3,"n_unverified":2,"n_honours":2,"n_violates":1,"n_no_contract":3,"n_pointer_only":2,"phrase":"9 ran (of which 0 constructed an object rather than computing a result; 6 with no instrument failure: 2 honoured, 1 violated, 3 with no contract checked; 3 where Syntology's instrument failed) · 2 unverified","sample_list":"/paper/do-multi-hop-readers-dream-of-reasoning#ran","syntology_url":"https://syntology.ai/paper/1910.14520","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1910.14520"}},"official":{"repos":["helloeve/bert-co-matching"],"state":"official (archive's flag): 9 ran","n_ran":9,"n_constructed":0,"n_ran_no_instrument_failure":6,"n_unverified":2,"ran_from_kinds":["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/on-the-cross-lingual-transferability-of","slug":"on-the-cross-lingual-transferability-of","title":"On the Cross-lingual Transferability of Monolingual Representations","date":"2019-10-25","arxiv_id":"1910.11856","repositories_listed":7,"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/on-the-cross-lingual-transferability-of#ran","syntology_url":"https://syntology.ai/paper/1910.11856","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1910.11856"}},"official":{"repos":["deepmind/xquad"],"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/exploring-the-limits-of-transfer-learning","slug":"exploring-the-limits-of-transfer-learning","title":"Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer","date":"2019-10-23","arxiv_id":"1910.10683","repositories_listed":57,"syntology":{"n":31,"n_ran":21,"n_constructed":0,"n_ran_checked":20,"n_instrument":1,"n_unverified":10,"n_honours":1,"n_violates":0,"n_no_contract":19,"n_pointer_only":0,"phrase":"21 ran (of which 0 constructed an object rather than computing a result; 20 with no instrument failure: 1 honoured, 0 violated, 19 with no contract checked; 1 where Syntology's instrument failed) · 10 unverified","sample_list":"/paper/exploring-the-limits-of-transfer-learning#ran","syntology_url":"https://syntology.ai/paper/1910.10683","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1910.10683"}},"official":null}},{"url":"/paper/mrqa-2019-shared-task-evaluating","slug":"mrqa-2019-shared-task-evaluating","title":"MRQA 2019 Shared Task: Evaluating Generalization in Reading Comprehension","date":"2019-10-22","arxiv_id":"1910.09753","repositories_listed":1,"syntology":{"n":3,"n_ran":3,"n_constructed":0,"n_ran_checked":2,"n_instrument":1,"n_unverified":0,"n_honours":1,"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; 2 with no instrument failure: 1 honoured, 1 violated, 0 with no contract checked; 1 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/mrqa-2019-shared-task-evaluating#ran","syntology_url":"https://syntology.ai/paper/1910.09753","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1910.09753"}},"official":{"repos":["mrqa/MRQA-Shared-Task-2019"],"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/mlqa-evaluating-cross-lingual-extractive","slug":"mlqa-evaluating-cross-lingual-extractive","title":"MLQA: Evaluating Cross-lingual Extractive Question Answering","date":"2019-10-16","arxiv_id":"1910.07475","repositories_listed":4,"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/mlqa-evaluating-cross-lingual-extractive#ran","syntology_url":"https://syntology.ai/paper/1910.07475","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1910.07475"}},"official":{"repos":["facebookresearch/MLQA"],"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/enhancing-the-transformer-with-explicit-1","slug":"enhancing-the-transformer-with-explicit-1","title":"Enhancing the Transformer with Explicit Relational Encoding for Math Problem Solving","date":"2019-10-15","arxiv_id":"1910.06611","repositories_listed":3,"syntology":{"n":11,"n_ran":8,"n_constructed":0,"n_ran_checked":8,"n_instrument":0,"n_unverified":3,"n_honours":1,"n_violates":0,"n_no_contract":7,"n_pointer_only":0,"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) · 3 unverified","sample_list":"/paper/enhancing-the-transformer-with-explicit-1#ran","syntology_url":"https://syntology.ai/paper/1910.06611","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1910.06611"}},"official":{"repos":["ischlag/TP-Transformer"],"state":"official (archive's flag): 8 ran","n_ran":8,"n_constructed":0,"n_ran_no_instrument_failure":8,"n_unverified":3,"ran_from_kinds":["official"]}}},{"url":"/paper/answering-complex-open-domain-questions","slug":"answering-complex-open-domain-questions","title":"Answering Complex Open-domain Questions Through Iterative Query Generation","date":"2019-10-15","arxiv_id":"1910.07000","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":1,"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: 0 honoured, 1 violated, 0 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/answering-complex-open-domain-questions#ran","syntology_url":"https://syntology.ai/paper/1910.07000","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1910.07000"}},"official":{"repos":["qipeng/golden-retriever"],"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/look-before-you-hop-conversational-question","slug":"look-before-you-hop-conversational-question","title":"Look before you Hop: Conversational Question Answering over Knowledge Graphs Using Judicious Context Expansion","date":"2019-10-08","arxiv_id":"1910.03262","repositories_listed":1,"syntology":{"n":7,"n_ran":7,"n_constructed":0,"n_ran_checked":7,"n_instrument":0,"n_unverified":0,"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) · 0 unverified","sample_list":"/paper/look-before-you-hop-conversational-question#ran","syntology_url":"https://syntology.ai/paper/1910.03262","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1910.03262"}},"official":{"repos":["PhilippChr/CONVEX"],"state":"official (archive's flag): 7 ran","n_ran":7,"n_constructed":0,"n_ran_no_instrument_failure":7,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/remind-your-neural-network-to-prevent","slug":"remind-your-neural-network-to-prevent","title":"REMIND Your Neural Network to Prevent Catastrophic Forgetting","date":"2019-10-06","arxiv_id":"1910.02509","repositories_listed":1,"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":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) · 1 unverified","sample_list":"/paper/remind-your-neural-network-to-prevent#ran","syntology_url":"https://syntology.ai/paper/1910.02509","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1910.02509"}},"official":{"repos":["tyler-hayes/REMIND"],"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"]}}},{"url":"/paper/distilbert-a-distilled-version-of-bert","slug":"distilbert-a-distilled-version-of-bert","title":"DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter","date":"2019-10-02","arxiv_id":"1910.01108","repositories_listed":37,"syntology":{"n":27,"n_ran":21,"n_constructed":5,"n_ran_checked":13,"n_instrument":8,"n_unverified":6,"n_honours":3,"n_violates":1,"n_no_contract":9,"n_pointer_only":2,"phrase":"21 ran (of which 5 constructed an object rather than computing a result; 13 with no instrument failure: 3 honoured, 1 violated, 9 with no contract checked; 8 where Syntology's instrument failed) · 6 unverified","sample_list":"/paper/distilbert-a-distilled-version-of-bert#ran","syntology_url":"https://syntology.ai/paper/1910.01108","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1910.01108"}},"official":{"repos":["huggingface/swift-coreml-transformers","huggingface/transformers"],"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/compact-trilinear-interaction-for-visual","slug":"compact-trilinear-interaction-for-visual","title":"Compact Trilinear Interaction for Visual Question Answering","date":"2019-09-26","arxiv_id":"1909.11874","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":1,"n_no_contract":2,"n_pointer_only":1,"phrase":"3 ran (of which 0 constructed an object rather than computing a result; 3 with no instrument failure: 0 honoured, 1 violated, 2 with no contract checked; 0 where Syntology's instrument failed) · 2 unverified","sample_list":"/paper/compact-trilinear-interaction-for-visual#ran","syntology_url":"https://syntology.ai/paper/1909.11874","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1909.11874"}},"official":{"repos":["aioz-ai/ICCV19_VQA-CTI"],"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/albert-a-lite-bert-for-self-supervised","slug":"albert-a-lite-bert-for-self-supervised","title":"ALBERT: A Lite BERT for Self-supervised Learning of Language Representations","date":"2019-09-26","arxiv_id":"1909.11942","repositories_listed":48,"syntology":{"n":126,"n_ran":81,"n_constructed":17,"n_ran_checked":59,"n_instrument":22,"n_unverified":45,"n_honours":4,"n_violates":0,"n_no_contract":55,"n_pointer_only":28,"phrase":"81 ran (of which 17 constructed an object rather than computing a result; 59 with no instrument failure: 4 honoured, 0 violated, 55 with no contract checked; 22 where Syntology's instrument failed) · 45 unverified","sample_list":"/paper/albert-a-lite-bert-for-self-supervised#ran","syntology_url":"https://syntology.ai/paper/1909.11942","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1909.11942"}},"official":{"repos":["google-research/ALBERT"],"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":["listed","official"]}}},{"url":"/paper/uniter-learning-universal-image-text-1","slug":"uniter-learning-universal-image-text-1","title":"UNITER: UNiversal Image-TExt Representation Learning","date":"2019-09-25","arxiv_id":"1909.11740","repositories_listed":7,"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/uniter-learning-universal-image-text-1#ran","syntology_url":"https://syntology.ai/paper/1909.11740","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1909.11740"}},"official":{"repos":["ChenRocks/UNITER"],"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/unified-vision-language-pre-training-for","slug":"unified-vision-language-pre-training-for","title":"Unified Vision-Language Pre-Training for Image Captioning and VQA","date":"2019-09-24","arxiv_id":"1909.11059","repositories_listed":3,"syntology":{"n":14,"n_ran":11,"n_constructed":0,"n_ran_checked":8,"n_instrument":3,"n_unverified":3,"n_honours":1,"n_violates":0,"n_no_contract":7,"n_pointer_only":14,"phrase":"11 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; 3 where Syntology's instrument failed) · 3 unverified","sample_list":"/paper/unified-vision-language-pre-training-for#ran","syntology_url":"https://syntology.ai/paper/1909.11059","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1909.11059"}},"official":{"repos":["LuoweiZhou/VLP"],"state":"official (archive's flag): 11 ran","n_ran":11,"n_constructed":0,"n_ran_no_instrument_failure":8,"n_unverified":3,"ran_from_kinds":["official"]}}},{"url":"/paper/portuguese-named-entity-recognition-using-1","slug":"portuguese-named-entity-recognition-using-1","title":"Portuguese Named Entity Recognition using BERT-CRF","date":"2019-09-23","arxiv_id":"1909.10649","repositories_listed":1,"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":3,"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/portuguese-named-entity-recognition-using-1#ran","syntology_url":"https://syntology.ai/paper/1909.10649","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1909.10649"}},"official":{"repos":["neuralmind-ai/portuguese-bert"],"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/megatron-lm-training-multi-billion-parameter","slug":"megatron-lm-training-multi-billion-parameter","title":"Megatron-LM: Training Multi-Billion Parameter Language Models Using Model Parallelism","date":"2019-09-17","arxiv_id":"1909.08053","repositories_listed":10,"syntology":{"n":47,"n_ran":12,"n_constructed":2,"n_ran_checked":7,"n_instrument":5,"n_unverified":35,"n_honours":4,"n_violates":0,"n_no_contract":3,"n_pointer_only":15,"phrase":"12 ran (of which 2 constructed an object rather than computing a result; 7 with no instrument failure: 4 honoured, 0 violated, 3 with no contract checked; 5 where Syntology's instrument failed) · 35 unverified","sample_list":"/paper/megatron-lm-training-multi-billion-parameter#ran","syntology_url":"https://syntology.ai/paper/1909.08053","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1909.08053"}},"official":{"repos":["NVIDIA/Megatron-LM"],"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/addressing-semantic-drift-in-question","slug":"addressing-semantic-drift-in-question","title":"Addressing Semantic Drift in Question Generation for Semi-Supervised Question Answering","date":"2019-09-13","arxiv_id":"1909.06356","repositories_listed":2,"syntology":{"n":19,"n_ran":13,"n_constructed":0,"n_ran_checked":11,"n_instrument":2,"n_unverified":6,"n_honours":2,"n_violates":1,"n_no_contract":8,"n_pointer_only":1,"phrase":"13 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; 2 where Syntology's instrument failed) · 6 unverified","sample_list":"/paper/addressing-semantic-drift-in-question#ran","syntology_url":"https://syntology.ai/paper/1909.06356","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1909.06356"}},"official":{"repos":["ZhangShiyue/QGforQA"],"state":"official (archive's flag): 13 ran","n_ran":13,"n_constructed":0,"n_ran_no_instrument_failure":11,"n_unverified":6,"ran_from_kinds":["official"]}}},{"url":"/paper/finding-generalizable-evidence-by-learning-to","slug":"finding-generalizable-evidence-by-learning-to","title":"Finding Generalizable Evidence by Learning to Convince Q&A Models","date":"2019-09-12","arxiv_id":"1909.05863","repositories_listed":1,"syntology":{"n":22,"n_ran":11,"n_constructed":0,"n_ran_checked":11,"n_instrument":0,"n_unverified":11,"n_honours":0,"n_violates":0,"n_no_contract":11,"n_pointer_only":4,"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) · 11 unverified","sample_list":"/paper/finding-generalizable-evidence-by-learning-to#ran","syntology_url":"https://syntology.ai/paper/1909.05863","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1909.05863"}},"official":{"repos":["ethanjperez/convince"],"state":"official (archive's flag): 11 ran","n_ran":11,"n_constructed":0,"n_ran_no_instrument_failure":11,"n_unverified":11,"ran_from_kinds":["official"]}}},{"url":"/paper/a-discrete-hard-em-approach-for-weakly","slug":"a-discrete-hard-em-approach-for-weakly","title":"A Discrete Hard EM Approach for Weakly Supervised Question Answering","date":"2019-09-11","arxiv_id":"1909.04849","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/a-discrete-hard-em-approach-for-weakly#ran","syntology_url":"https://syntology.ai/paper/1909.04849","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1909.04849"}},"official":{"repos":["shmsw25/qa-hard-em"],"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/how-does-bert-answer-questions-a-layer-wise","slug":"how-does-bert-answer-questions-a-layer-wise","title":"How Does BERT Answer Questions? A Layer-Wise Analysis of Transformer Representations","date":"2019-09-11","arxiv_id":"1909.04925","repositories_listed":2,"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/how-does-bert-answer-questions-a-layer-wise#ran","syntology_url":"https://syntology.ai/paper/1909.04925","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1909.04925"}},"official":{"repos":["bvanaken/explain-BERT-QA"],"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/dont-take-the-easy-way-out-ensemble-based","slug":"dont-take-the-easy-way-out-ensemble-based","title":"Don't Take the Easy Way Out: Ensemble Based Methods for Avoiding Known Dataset Biases","date":"2019-09-09","arxiv_id":"1909.03683","repositories_listed":3,"syntology":{"n":6,"n_ran":4,"n_constructed":0,"n_ran_checked":1,"n_instrument":3,"n_unverified":2,"n_honours":0,"n_violates":0,"n_no_contract":1,"n_pointer_only":3,"phrase":"4 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; 3 where Syntology's instrument failed) · 2 unverified","sample_list":"/paper/dont-take-the-easy-way-out-ensemble-based#ran","syntology_url":"https://syntology.ai/paper/1909.03683","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1909.03683"}},"official":{"repos":["chrisc36/debias"],"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":["listed","official"]}}},{"url":"/paper/span-selection-pre-training-for-question","slug":"span-selection-pre-training-for-question","title":"Span Selection Pre-training for Question Answering","date":"2019-09-09","arxiv_id":"1909.04120","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/span-selection-pre-training-for-question#ran","syntology_url":"https://syntology.ai/paper/1909.04120","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1909.04120"}},"official":{"repos":["IBM/span-selection-pretraining"],"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/question-generation-by-transformers","slug":"question-generation-by-transformers","title":"Question Generation by Transformers","date":"2019-09-09","arxiv_id":"1909.05017","repositories_listed":1,"syntology":{"n":14,"n_ran":5,"n_constructed":0,"n_ran_checked":4,"n_instrument":1,"n_unverified":9,"n_honours":0,"n_violates":0,"n_no_contract":4,"n_pointer_only":0,"phrase":"5 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; 1 where Syntology's instrument failed) · 9 unverified","sample_list":"/paper/question-generation-by-transformers#ran","syntology_url":"https://syntology.ai/paper/1909.05017","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1909.05017"}},"official":null}},{"url":"/paper/graph-based-reasoning-over-heterogeneous","slug":"graph-based-reasoning-over-heterogeneous","title":"Graph-Based Reasoning over Heterogeneous External Knowledge for Commonsense Question Answering","date":"2019-09-09","arxiv_id":"1909.05311","repositories_listed":1,"syntology":{"n":17,"n_ran":12,"n_constructed":0,"n_ran_checked":7,"n_instrument":5,"n_unverified":5,"n_honours":2,"n_violates":0,"n_no_contract":5,"n_pointer_only":2,"phrase":"12 ran (of which 0 constructed an object rather than computing a result; 7 with no instrument failure: 2 honoured, 0 violated, 5 with no contract checked; 5 where Syntology's instrument failed) · 5 unverified","sample_list":"/paper/graph-based-reasoning-over-heterogeneous#ran","syntology_url":"https://syntology.ai/paper/1909.05311","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1909.05311"}},"official":{"repos":["DecstionBack/AAAI_2020_CommonsenseQA"],"state":"official (archive's flag): 12 ran","n_ran":12,"n_constructed":0,"n_ran_no_instrument_failure":7,"n_unverified":5,"ran_from_kinds":["official"]}}},{"url":"/paper/semantics-aware-bert-for-language","slug":"semantics-aware-bert-for-language","title":"Semantics-aware BERT for Language Understanding","date":"2019-09-05","arxiv_id":"1909.02209","repositories_listed":1,"syntology":{"n":12,"n_ran":7,"n_constructed":0,"n_ran_checked":5,"n_instrument":2,"n_unverified":5,"n_honours":2,"n_violates":0,"n_no_contract":3,"n_pointer_only":3,"phrase":"7 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; 2 where Syntology's instrument failed) · 5 unverified","sample_list":"/paper/semantics-aware-bert-for-language#ran","syntology_url":"https://syntology.ai/paper/1909.02209","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1909.02209"}},"official":{"repos":["cooelf/SemBERT"],"state":"official (archive's flag): 7 ran","n_ran":7,"n_constructed":0,"n_ran_no_instrument_failure":5,"n_unverified":5,"ran_from_kinds":["official"]}}},{"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/interactive-language-learning-by-question","slug":"interactive-language-learning-by-question","title":"Interactive Language Learning by Question Answering","date":"2019-08-28","arxiv_id":"1908.10909","repositories_listed":1,"syntology":{"n":11,"n_ran":10,"n_constructed":0,"n_ran_checked":8,"n_instrument":2,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":8,"n_pointer_only":10,"phrase":"10 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; 2 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/interactive-language-learning-by-question#ran","syntology_url":"https://syntology.ai/paper/1908.10909","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1908.10909"}},"official":{"repos":["xingdi-eric-yuan/qait_public"],"state":"official (archive's flag): 10 ran","n_ran":10,"n_constructed":0,"n_ran_no_instrument_failure":8,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/interactive-machine-comprehension-with","slug":"interactive-machine-comprehension-with","title":"Interactive Machine Comprehension with Information Seeking Agents","date":"2019-08-27","arxiv_id":"1908.10449","repositories_listed":1,"syntology":{"n":6,"n_ran":6,"n_constructed":0,"n_ran_checked":5,"n_instrument":1,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":5,"n_pointer_only":6,"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) · 0 unverified","sample_list":"/paper/interactive-machine-comprehension-with#ran","syntology_url":"https://syntology.ai/paper/1908.10449","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1908.10449"}},"official":{"repos":["xingdi-eric-yuan/imrc_public"],"state":"official (archive's flag): 6 ran","n_ran":6,"n_constructed":0,"n_ran_no_instrument_failure":5,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/vl-bert-pre-training-of-generic-visual","slug":"vl-bert-pre-training-of-generic-visual","title":"VL-BERT: Pre-training of Generic Visual-Linguistic Representations","date":"2019-08-22","arxiv_id":"1908.08530","repositories_listed":3,"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":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) · 0 unverified","sample_list":"/paper/vl-bert-pre-training-of-generic-visual#ran","syntology_url":"https://syntology.ai/paper/1908.08530","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1908.08530"}},"official":{"repos":["jackroos/VL-BERT"],"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/lxmert-learning-cross-modality-encoder","slug":"lxmert-learning-cross-modality-encoder","title":"LXMERT: Learning Cross-Modality Encoder Representations from Transformers","date":"2019-08-20","arxiv_id":"1908.07490","repositories_listed":9,"syntology":{"n":15,"n_ran":4,"n_constructed":4,"n_ran_checked":4,"n_instrument":0,"n_unverified":11,"n_honours":0,"n_violates":0,"n_no_contract":4,"n_pointer_only":3,"phrase":"4 ran (of which 4 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) · 11 unverified; every one of the 4 samples that ran constructed an object rather than computing a result","sample_list":"/paper/lxmert-learning-cross-modality-encoder#ran","syntology_url":"https://syntology.ai/paper/1908.07490","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1908.07490"}},"official":{"repos":["airsplay/lxmert"],"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/abductive-commonsense-reasoning","slug":"abductive-commonsense-reasoning","title":"Abductive Commonsense Reasoning","date":"2019-08-15","arxiv_id":"1908.05739","repositories_listed":2,"syntology":{"n":15,"n_ran":14,"n_constructed":0,"n_ran_checked":12,"n_instrument":2,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":12,"n_pointer_only":2,"phrase":"14 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; 2 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/abductive-commonsense-reasoning#ran","syntology_url":"https://syntology.ai/paper/1908.05739","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1908.05739"}},"official":null}},{"url":"/paper/vilbert-pretraining-task-agnostic","slug":"vilbert-pretraining-task-agnostic","title":"ViLBERT: Pretraining Task-Agnostic Visiolinguistic Representations for Vision-and-Language Tasks","date":"2019-08-06","arxiv_id":"1908.02265","repositories_listed":11,"syntology":{"n":34,"n_ran":10,"n_constructed":6,"n_ran_checked":8,"n_instrument":2,"n_unverified":24,"n_honours":0,"n_violates":0,"n_no_contract":8,"n_pointer_only":34,"phrase":"10 ran (of which 6 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) · 24 unverified","sample_list":"/paper/vilbert-pretraining-task-agnostic#ran","syntology_url":"https://syntology.ai/paper/1908.02265","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1908.02265"}},"official":null}},{"url":"/paper/simple-and-effective-text-matching-with-1","slug":"simple-and-effective-text-matching-with-1","title":"Simple and Effective Text Matching with Richer Alignment Features","date":"2019-08-01","arxiv_id":"1908.00300","repositories_listed":3,"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/simple-and-effective-text-matching-with-1#ran","syntology_url":"https://syntology.ai/paper/1908.00300","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1908.00300"}},"official":{"repos":["hitvoice/RE2"],"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/a-translate-edit-model-for-natural-language","slug":"a-translate-edit-model-for-natural-language","title":"Text-to-SQL Generation for Question Answering on Electronic Medical Records","date":"2019-07-28","arxiv_id":"1908.01839","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":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) · 0 unverified","sample_list":"/paper/a-translate-edit-model-for-natural-language#ran","syntology_url":"https://syntology.ai/paper/1908.01839","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1908.01839"}},"official":{"repos":["wangpinggl/TREQS"],"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/roberta-a-robustly-optimized-bert-pretraining","slug":"roberta-a-robustly-optimized-bert-pretraining","title":"RoBERTa: A Robustly Optimized BERT Pretraining Approach","date":"2019-07-26","arxiv_id":"1907.11692","repositories_listed":67,"syntology":{"n":48,"n_ran":37,"n_constructed":11,"n_ran_checked":36,"n_instrument":1,"n_unverified":11,"n_honours":0,"n_violates":0,"n_no_contract":36,"n_pointer_only":24,"phrase":"37 ran (of which 11 constructed an object rather than computing a result; 36 with no instrument failure: 0 honoured, 0 violated, 36 with no contract checked; 1 where Syntology's instrument failed) · 11 unverified","sample_list":"/paper/roberta-a-robustly-optimized-bert-pretraining#ran","syntology_url":"https://syntology.ai/paper/1907.11692","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1907.11692"}},"official":{"repos":["pytorch/fairseq"],"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/spanbert-improving-pre-training-by","slug":"spanbert-improving-pre-training-by","title":"SpanBERT: Improving Pre-training by Representing and Predicting Spans","date":"2019-07-24","arxiv_id":"1907.10529","repositories_listed":6,"syntology":{"n":15,"n_ran":9,"n_constructed":0,"n_ran_checked":6,"n_instrument":3,"n_unverified":6,"n_honours":0,"n_violates":0,"n_no_contract":6,"n_pointer_only":6,"phrase":"9 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; 3 where Syntology's instrument failed) · 6 unverified","sample_list":"/paper/spanbert-improving-pre-training-by#ran","syntology_url":"https://syntology.ai/paper/1907.10529","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1907.10529"}},"official":{"repos":["facebookresearch/SpanBERT"],"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":["listed","official"]}}},{"url":"/paper/eli5-long-form-question-answering","slug":"eli5-long-form-question-answering","title":"ELI5: Long Form Question Answering","date":"2019-07-22","arxiv_id":"1907.09190","repositories_listed":3,"syntology":{"n":11,"n_ran":10,"n_constructed":0,"n_ran_checked":7,"n_instrument":3,"n_unverified":1,"n_honours":0,"n_violates":1,"n_no_contract":6,"n_pointer_only":4,"phrase":"10 ran (of which 0 constructed an object rather than computing a result; 7 with no instrument failure: 0 honoured, 1 violated, 6 with no contract checked; 3 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/eli5-long-form-question-answering#ran","syntology_url":"https://syntology.ai/paper/1907.09190","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1907.09190"}},"official":{"repos":["facebookresearch/ELI5"],"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/neural-shuffle-exchange-networks-sequence","slug":"neural-shuffle-exchange-networks-sequence","title":"Neural Shuffle-Exchange Networks -- Sequence Processing in O(n log n) Time","date":"2019-07-18","arxiv_id":"1907.07897","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/neural-shuffle-exchange-networks-sequence#ran","syntology_url":"https://syntology.ai/paper/1907.07897","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1907.07897"}},"official":{"repos":["LUMII-Syslab/shuffle-exchange"],"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/a-self-attentive-model-for-knowledge-tracing","slug":"a-self-attentive-model-for-knowledge-tracing","title":"A Self-Attentive model for Knowledge Tracing","date":"2019-07-16","arxiv_id":"1907.06837","repositories_listed":10,"syntology":{"n":12,"n_ran":8,"n_constructed":0,"n_ran_checked":4,"n_instrument":4,"n_unverified":4,"n_honours":0,"n_violates":2,"n_no_contract":2,"n_pointer_only":9,"phrase":"8 ran (of which 0 constructed an object rather than computing a result; 4 with no instrument failure: 0 honoured, 2 violated, 2 with no contract checked; 4 where Syntology's instrument failed) · 4 unverified","sample_list":"/paper/a-self-attentive-model-for-knowledge-tracing#ran","syntology_url":"https://syntology.ai/paper/1907.06837","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1907.06837"}},"official":null}},{"url":"/paper/reqa-an-evaluation-for-end-to-end-answer","slug":"reqa-an-evaluation-for-end-to-end-answer","title":"ReQA: An Evaluation for End-to-End Answer Retrieval Models","date":"2019-07-10","arxiv_id":"1907.04780","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/reqa-an-evaluation-for-end-to-end-answer#ran","syntology_url":"https://syntology.ai/paper/1907.04780","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1907.04780"}},"official":{"repos":["google/retrieval-qa-eval"],"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/deep-modular-co-attention-networks-for-visual-1","slug":"deep-modular-co-attention-networks-for-visual-1","title":"Deep Modular Co-Attention Networks for Visual Question Answering","date":"2019-06-25","arxiv_id":"1906.10770","repositories_listed":7,"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":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) · 0 unverified","sample_list":"/paper/deep-modular-co-attention-networks-for-visual-1#ran","syntology_url":"https://syntology.ai/paper/1906.10770","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1906.10770"}},"official":{"repos":["MILVLG/mcan-vqa"],"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/adversarial-regularization-for-visual","slug":"adversarial-regularization-for-visual","title":"Adversarial Regularization for Visual Question Answering: Strengths, Shortcomings, and Side Effects","date":"2019-06-20","arxiv_id":"1906.08430","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/adversarial-regularization-for-visual#ran","syntology_url":"https://syntology.ai/paper/1906.08430","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1906.08430"}},"official":{"repos":["gabegrand/adversarial-vqa"],"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","unlocated"]}}},{"url":"/paper/xlnet-generalized-autoregressive-pretraining","slug":"xlnet-generalized-autoregressive-pretraining","title":"XLNet: Generalized Autoregressive Pretraining for Language Understanding","date":"2019-06-19","arxiv_id":"1906.08237","repositories_listed":27,"syntology":{"n":24,"n_ran":15,"n_constructed":2,"n_ran_checked":10,"n_instrument":5,"n_unverified":9,"n_honours":2,"n_violates":0,"n_no_contract":8,"n_pointer_only":4,"phrase":"15 ran (of which 2 constructed an object rather than computing a result; 10 with no instrument failure: 2 honoured, 0 violated, 8 with no contract checked; 5 where Syntology's instrument failed) · 9 unverified","sample_list":"/paper/xlnet-generalized-autoregressive-pretraining#ran","syntology_url":"https://syntology.ai/paper/1906.08237","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1906.08237"}},"official":{"repos":["zihangdai/xlnet"],"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":["listed","official"]}}},{"url":"/paper/avoiding-reasoning-shortcuts-adversarial","slug":"avoiding-reasoning-shortcuts-adversarial","title":"Avoiding Reasoning Shortcuts: Adversarial Evaluation, Training, and Model Development for Multi-Hop QA","date":"2019-06-17","arxiv_id":"1906.07132","repositories_listed":1,"syntology":{"n":13,"n_ran":11,"n_constructed":0,"n_ran_checked":11,"n_instrument":0,"n_unverified":2,"n_honours":0,"n_violates":0,"n_no_contract":11,"n_pointer_only":0,"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) · 2 unverified","sample_list":"/paper/avoiding-reasoning-shortcuts-adversarial#ran","syntology_url":"https://syntology.ai/paper/1906.07132","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1906.07132"}},"official":{"repos":["jiangycTarheel/Adversarial-MultiHopQA"],"state":"official (archive's flag): 11 ran","n_ran":11,"n_constructed":0,"n_ran_no_instrument_failure":11,"n_unverified":2,"ran_from_kinds":["official"]}}},{"url":"/paper/nlprolog-reasoning-with-weak-unification-for-1","slug":"nlprolog-reasoning-with-weak-unification-for-1","title":"NLProlog: Reasoning with Weak Unification for Question Answering in Natural Language","date":"2019-06-14","arxiv_id":"1906.06187","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":0,"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/nlprolog-reasoning-with-weak-unification-for-1#ran","syntology_url":"https://syntology.ai/paper/1906.06187","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1906.06187"}},"official":{"repos":["leonweber/nlprolog"],"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/real-time-open-domain-question-answering-with","slug":"real-time-open-domain-question-answering-with","title":"Real-Time Open-Domain Question Answering with Dense-Sparse Phrase Index","date":"2019-06-13","arxiv_id":"1906.05807","repositories_listed":1,"syntology":{"n":19,"n_ran":16,"n_constructed":0,"n_ran_checked":14,"n_instrument":2,"n_unverified":3,"n_honours":4,"n_violates":1,"n_no_contract":9,"n_pointer_only":4,"phrase":"16 ran (of which 0 constructed an object rather than computing a result; 14 with no instrument failure: 4 honoured, 1 violated, 9 with no contract checked; 2 where Syntology's instrument failed) · 3 unverified","sample_list":"/paper/real-time-open-domain-question-answering-with#ran","syntology_url":"https://syntology.ai/paper/1906.05807","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1906.05807"}},"official":{"repos":["uwnlp/denspi"],"state":"official (archive's flag): 16 ran","n_ran":16,"n_constructed":0,"n_ran_no_instrument_failure":14,"n_unverified":3,"ran_from_kinds":["official"]}}},{"url":"/paper/neural-arabic-question-answering","slug":"neural-arabic-question-answering","title":"Neural Arabic Question Answering","date":"2019-06-12","arxiv_id":"1906.05394","repositories_listed":1,"syntology":{"n":7,"n_ran":6,"n_constructed":0,"n_ran_checked":5,"n_instrument":1,"n_unverified":1,"n_honours":2,"n_violates":0,"n_no_contract":3,"n_pointer_only":2,"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) · 1 unverified","sample_list":"/paper/neural-arabic-question-answering#ran","syntology_url":"https://syntology.ai/paper/1906.05394","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1906.05394"}},"official":{"repos":["husseinmozannar/SOQAL"],"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/retrieve-read-rerank-towards-end-to-end-multi","slug":"retrieve-read-rerank-towards-end-to-end-multi","title":"Retrieve, Read, Rerank: Towards End-to-End Multi-Document Reading Comprehension","date":"2019-06-11","arxiv_id":"1906.04618","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/retrieve-read-rerank-towards-end-to-end-multi#ran","syntology_url":"https://syntology.ai/paper/1906.04618","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1906.04618"}},"official":{"repos":["huminghao16/RE3QA"],"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/episodic-memory-in-lifelong-language-learning","slug":"episodic-memory-in-lifelong-language-learning","title":"Episodic Memory in Lifelong Language Learning","date":"2019-06-03","arxiv_id":"1906.01076","repositories_listed":2,"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/episodic-memory-in-lifelong-language-learning#ran","syntology_url":"https://syntology.ai/paper/1906.01076","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1906.01076"}},"official":null}},{"url":"/paper/a-generalized-framework-of-sequence","slug":"a-generalized-framework-of-sequence","title":"A Generalized Framework of Sequence Generation with Application to Undirected Sequence Models","date":"2019-05-29","arxiv_id":"1905.12790","repositories_listed":1,"syntology":{"n":3,"n_ran":3,"n_constructed":2,"n_ran_checked":1,"n_instrument":2,"n_unverified":0,"n_honours":1,"n_violates":0,"n_no_contract":0,"n_pointer_only":1,"phrase":"3 ran (of which 2 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/a-generalized-framework-of-sequence#ran","syntology_url":"https://syntology.ai/paper/1905.12790","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1905.12790"}},"official":{"repos":["nyu-dl/dl4mt-seqgen"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":1,"n_ran_no_instrument_failure":1,"n_unverified":0,"ran_from_kinds":["official","unlocated"]}}},{"url":"/paper/neural-stored-program-memory","slug":"neural-stored-program-memory","title":"Neural Stored-program Memory","date":"2019-05-25","arxiv_id":"1906.08862","repositories_listed":1,"syntology":{"n":4,"n_ran":1,"n_constructed":0,"n_ran_checked":1,"n_instrument":0,"n_unverified":3,"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) · 3 unverified","sample_list":"/paper/neural-stored-program-memory#ran","syntology_url":"https://syntology.ai/paper/1906.08862","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1906.08862"}},"official":{"repos":["thaihungle/NSM"],"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/dynamically-fused-graph-network-for-multi-hop","slug":"dynamically-fused-graph-network-for-multi-hop","title":"Dynamically Fused Graph Network for Multi-hop Reasoning","date":"2019-05-16","arxiv_id":"1905.06933","repositories_listed":1,"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":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) · 2 unverified","sample_list":"/paper/dynamically-fused-graph-network-for-multi-hop#ran","syntology_url":"https://syntology.ai/paper/1905.06933","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1905.06933"}},"official":{"repos":["woshiyyya/DFGN-pytorch"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":2,"ran_from_kinds":["official"]}}},{"url":"/paper/cognitive-graph-for-multi-hop-reading","slug":"cognitive-graph-for-multi-hop-reading","title":"Cognitive Graph for Multi-Hop Reading Comprehension at Scale","date":"2019-05-14","arxiv_id":"1905.05460","repositories_listed":2,"syntology":{"n":9,"n_ran":7,"n_constructed":0,"n_ran_checked":5,"n_instrument":2,"n_unverified":2,"n_honours":1,"n_violates":2,"n_no_contract":2,"n_pointer_only":1,"phrase":"7 ran (of which 0 constructed an object rather than computing a result; 5 with no instrument failure: 1 honoured, 2 violated, 2 with no contract checked; 2 where Syntology's instrument failed) · 2 unverified","sample_list":"/paper/cognitive-graph-for-multi-hop-reading#ran","syntology_url":"https://syntology.ai/paper/1905.05460","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1905.05460"}},"official":{"repos":["THUDM/CogQA"],"state":"official (archive's flag): 5 ran","n_ran":5,"n_constructed":0,"n_ran_no_instrument_failure":4,"n_unverified":2,"ran_from_kinds":["listed","official"]}}},{"url":"/paper/multi-step-retriever-reader-interaction-for-1","slug":"multi-step-retriever-reader-interaction-for-1","title":"Multi-step Retriever-Reader Interaction for Scalable Open-domain Question Answering","date":"2019-05-14","arxiv_id":"1905.05733","repositories_listed":1,"syntology":{"n":10,"n_ran":8,"n_constructed":0,"n_ran_checked":8,"n_instrument":0,"n_unverified":2,"n_honours":0,"n_violates":1,"n_no_contract":7,"n_pointer_only":0,"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) · 2 unverified","sample_list":"/paper/multi-step-retriever-reader-interaction-for-1#ran","syntology_url":"https://syntology.ai/paper/1905.05733","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1905.05733"}},"official":{"repos":["rajarshd/Multi-Step-Reasoning"],"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/routing-networks-and-the-challenges-of","slug":"routing-networks-and-the-challenges-of","title":"Routing Networks and the Challenges of Modular and Compositional Computation","date":"2019-04-29","arxiv_id":"1904.12774","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/routing-networks-and-the-challenges-of#ran","syntology_url":"https://syntology.ai/paper/1904.12774","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1904.12774"}},"official":null}},{"url":"/paper/the-neuro-symbolic-concept-learner-1","slug":"the-neuro-symbolic-concept-learner-1","title":"The Neuro-Symbolic Concept Learner: Interpreting Scenes, Words, and Sentences From Natural Supervision","date":"2019-04-26","arxiv_id":"1904.12584","repositories_listed":2,"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-neuro-symbolic-concept-learner-1#ran","syntology_url":"https://syntology.ai/paper/1904.12584","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1904.12584"}},"official":{"repos":["vacancy/NSCL-PyTorch-Release"],"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/tvqa-spatio-temporal-grounding-for-video","slug":"tvqa-spatio-temporal-grounding-for-video","title":"TVQA+: Spatio-Temporal Grounding for Video Question Answering","date":"2019-04-25","arxiv_id":"1904.11574","repositories_listed":3,"syntology":{"n":13,"n_ran":12,"n_constructed":0,"n_ran_checked":8,"n_instrument":4,"n_unverified":1,"n_honours":1,"n_violates":0,"n_no_contract":7,"n_pointer_only":2,"phrase":"12 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; 4 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/tvqa-spatio-temporal-grounding-for-video#ran","syntology_url":"https://syntology.ai/paper/1904.11574","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1904.11574"}},"official":{"repos":["jayleicn/TVQA-PLUS","jayleicn/TVQAplus"],"state":"official (archive's flag): 12 ran","n_ran":12,"n_constructed":0,"n_ran_no_instrument_failure":8,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/scene-graph-prediction-with-limited-labels","slug":"scene-graph-prediction-with-limited-labels","title":"Scene Graph Prediction with Limited Labels","date":"2019-04-25","arxiv_id":"1904.11622","repositories_listed":1,"syntology":{"n":6,"n_ran":4,"n_constructed":0,"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 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) · 2 unverified","sample_list":"/paper/scene-graph-prediction-with-limited-labels#ran","syntology_url":"https://syntology.ai/paper/1904.11622","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1904.11622"}},"official":null}},{"url":"/paper/improving-differentiable-neural-computers-1","slug":"improving-differentiable-neural-computers-1","title":"Improving Differentiable Neural Computers Through Memory Masking, De-allocation, and Link Distribution Sharpness Control","date":"2019-04-23","arxiv_id":"1904.10278","repositories_listed":1,"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":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) · 0 unverified","sample_list":"/paper/improving-differentiable-neural-computers-1#ran","syntology_url":"https://syntology.ai/paper/1904.10278","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1904.10278"}},"official":{"repos":["robertcsordas/dnc"],"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/190410509","slug":"190410509","title":"Generating Long Sequences with Sparse Transformers","date":"2019-04-23","arxiv_id":"1904.10509","repositories_listed":7,"syntology":{"n":6,"n_ran":5,"n_constructed":4,"n_ran_checked":4,"n_instrument":1,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":4,"n_pointer_only":0,"phrase":"5 ran (of which 4 constructed an object rather than computing a result; 4 with no instrument failure: 0 honoured, 0 violated, 4 with no contract checked; 1 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/190410509#ran","syntology_url":"https://syntology.ai/paper/1904.10509","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1904.10509"}},"official":{"repos":["openai/sparse_attention"],"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/socialiqa-commonsense-reasoning-about-social","slug":"socialiqa-commonsense-reasoning-about-social","title":"SocialIQA: Commonsense Reasoning about Social Interactions","date":"2019-04-22","arxiv_id":"1904.09728","repositories_listed":1,"syntology":{"n":10,"n_ran":5,"n_constructed":0,"n_ran_checked":5,"n_instrument":0,"n_unverified":5,"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) · 5 unverified","sample_list":"/paper/socialiqa-commonsense-reasoning-about-social#ran","syntology_url":"https://syntology.ai/paper/1904.09728","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1904.09728"}},"official":null}},{"url":"/paper/ernie-enhanced-representation-through","slug":"ernie-enhanced-representation-through","title":"ERNIE: Enhanced Representation through Knowledge Integration","date":"2019-04-19","arxiv_id":"1904.09223","repositories_listed":19,"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/ernie-enhanced-representation-through#ran","syntology_url":"https://syntology.ai/paper/1904.09223","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1904.09223"}},"official":{"repos":["PaddlePaddle/PaddleNLP"],"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/document-expansion-by-query-prediction","slug":"document-expansion-by-query-prediction","title":"Document Expansion by Query Prediction","date":"2019-04-17","arxiv_id":"1904.08375","repositories_listed":5,"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/document-expansion-by-query-prediction#ran","syntology_url":"https://syntology.ai/paper/1904.08375","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1904.08375"}},"official":{"repos":["nyu-dl/dl4ir-doc2query"],"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/quizbowl-the-case-for-incremental-question","slug":"quizbowl-the-case-for-incremental-question","title":"Quizbowl: The Case for Incremental Question Answering","date":"2019-04-09","arxiv_id":"1904.04792","repositories_listed":1,"syntology":{"n":14,"n_ran":14,"n_constructed":0,"n_ran_checked":14,"n_instrument":0,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":14,"n_pointer_only":0,"phrase":"14 ran (of which 0 constructed an object rather than computing a result; 14 with no instrument failure: 0 honoured, 0 violated, 14 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/quizbowl-the-case-for-incremental-question#ran","syntology_url":"https://syntology.ai/paper/1904.04792","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1904.04792"}},"official":null}},{"url":"/paper/heterogeneous-memory-enhanced-multimodal","slug":"heterogeneous-memory-enhanced-multimodal","title":"Heterogeneous Memory Enhanced Multimodal Attention Model for Video Question Answering","date":"2019-04-08","arxiv_id":"1904.04357","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/heterogeneous-memory-enhanced-multimodal#ran","syntology_url":"https://syntology.ai/paper/1904.04357","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1904.04357"}},"official":{"repos":["fanchenyou/HME-VideoQA"],"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/habitat-a-platform-for-embodied-ai-research","slug":"habitat-a-platform-for-embodied-ai-research","title":"Habitat: A Platform for Embodied AI Research","date":"2019-04-02","arxiv_id":"1904.01201","repositories_listed":13,"syntology":{"n":15,"n_ran":13,"n_constructed":0,"n_ran_checked":11,"n_instrument":2,"n_unverified":2,"n_honours":0,"n_violates":0,"n_no_contract":11,"n_pointer_only":15,"phrase":"13 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; 2 where Syntology's instrument failed) · 2 unverified","sample_list":"/paper/habitat-a-platform-for-embodied-ai-research#ran","syntology_url":"https://syntology.ai/paper/1904.01201","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1904.01201"}},"official":{"repos":["facebookresearch/habitat-sim"],"state":"community repositories only","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["listed"]}}}],"record_sha256":"b5eac0eba91029c5c066a7e335ab028ee88c08719200b8c92de3fb3c0f7b7c6c","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}