{"about":{"site":"https://codewithpapers.app","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.","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"},"url":"/code/metadata-collate-fn","entry":"metadata_collate_fn","source":"Syntology graph, per-sample; not an archive number","read_at":"2026-09-24T18:15:14+00:00","claim":"Names are grouped by exact entry-name string. Same-named routines are NOT asserted to be equivalent; 'ran' means executed on a synthesized fixture, not correctness. n_samples_ran = sum of by_status over every status except 'unverified' (ran_draft_wrong and ran_fixture are failures of Syntology's instrument, not of the code); n_papers_ran = papers with at least one such sample.","status_vocabulary":{"ran_honours":"ran, honoured the contract we drafted","ran_violates":"ran, violated the contract we drafted","ran_draft_wrong":"ran; our contract draft was wrong, not the code","ran_fixture":"ran; our fixture could not drive it","ran":"ran on a synthesized input","unverified":"unverified (harvested, no recorded run)"},"n_papers":5,"n_papers_ran":5,"units":"n_samples, n_samples_ran, n_samples_fingerprinted and by_status count distinct code bodies (code_sha256); n_places and n_places_pointer_only count places, one per (paper, code body) pair, which is also the unit of the samples list","n_samples":1,"n_samples_ran":1,"n_samples_fingerprinted":0,"n_places":5,"n_places_pointer_only":0,"by_status":{"ran_honours":0,"ran_violates":0,"ran_draft_wrong":1,"ran_fixture":0,"ran":0,"unverified":0},"syntology":{"atlas_url":null,"mcp":null,"mcp_per_sample":{"tool":"get_code","arguments_in":"samples[].mcp_get_code"},"developers":"https://syntology.ai/developers"},"samples":[{"arxiv_id":"2404.02827","paper":"/paper/badam-a-memory-efficient-full-parameter","title":"BAdam: A Memory Efficient Full Parameter Optimization Method for Large Language Models","date":"2024-04-03","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"ledzy/badam","path":"roberta-superglue/jiant/tasks/core.py","file_url":"https://github.com/ledzy/badam/blob/HEAD/roberta-superglue/jiant/tasks/core.py","status":"ran_draft_wrong","verification_level":1,"contract_check":"OUTPUT_MISDECLARED","metamorphic_tier":"deterministic","behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"code_sha256_prefix":"61ffc5549a75fe3c","mcp_get_code":{"code_sha256":"61ffc5549a75fe3c"}},{"arxiv_id":"2112.01753","paper":"/paper/probing-linguistic-information-for-logical","title":"Probing Linguistic Information For Logical Inference In Pre-trained Language Models","date":"2021-12-03","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"eric11eca/inference-information-probing","path":"jiant/tasks/core.py","file_url":"https://github.com/eric11eca/inference-information-probing/blob/HEAD/jiant/tasks/core.py","status":"ran_draft_wrong","verification_level":1,"contract_check":"OUTPUT_MISDECLARED","metamorphic_tier":"deterministic","behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"61ffc5549a75fe3c","mcp_get_code":{"code_sha256":"61ffc5549a75fe3c"}},{"arxiv_id":"2010.04762","paper":"/paper/counterfactually-augmented-snli-training-data","title":"Counterfactually-Augmented SNLI Training Data Does Not Yield Better Generalization Than Unaugmented Data","date":"2020-10-09","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"nyu-mll/CNLI-generalization","path":"jiant/jiant/tasks/core.py","file_url":"https://github.com/nyu-mll/CNLI-generalization/blob/HEAD/jiant/jiant/tasks/core.py","status":"ran_draft_wrong","verification_level":1,"contract_check":"OUTPUT_MISDECLARED","metamorphic_tier":"deterministic","behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"61ffc5549a75fe3c","mcp_get_code":{"code_sha256":"61ffc5549a75fe3c"}},{"arxiv_id":"2003.02249","paper":"/paper/jiant-a-software-toolkit-for-research-on","title":"jiant: A Software Toolkit for Research on General-Purpose Text Understanding Models","date":"2020-03-04","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"nyu-mll/jiant","path":"jiant/proj/main/modeling/primary.py","file_url":"https://github.com/nyu-mll/jiant/blob/HEAD/jiant/proj/main/modeling/primary.py","status":"ran_draft_wrong","verification_level":1,"contract_check":"OUTPUT_MISDECLARED","metamorphic_tier":"deterministic","behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"61ffc5549a75fe3c","mcp_get_code":{"code_sha256":"61ffc5549a75fe3c"}},{"arxiv_id":"1804.07461","paper":"/paper/glue-a-multi-task-benchmark-and-analysis","title":"GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding","date":"2018-04-20","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"jsalt18-sentence-repl/jiant","path":"jiant/tasks/core.py","file_url":"https://github.com/jsalt18-sentence-repl/jiant/blob/HEAD/jiant/tasks/core.py","status":"ran_draft_wrong","verification_level":1,"contract_check":"OUTPUT_MISDECLARED","metamorphic_tier":"deterministic","behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"61ffc5549a75fe3c","mcp_get_code":{"code_sha256":"61ffc5549a75fe3c"}}]}