{"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/parse-date","entry":"parse_date","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":3,"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":5,"n_samples_ran":3,"n_samples_fingerprinted":2,"n_places":5,"n_places_pointer_only":2,"by_status":{"ran_honours":0,"ran_violates":0,"ran_draft_wrong":2,"ran_fixture":0,"ran":1,"unverified":2},"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":"2506.20920","paper":"/paper/fineweb2-one-pipeline-to-scale-them-all","title":"FineWeb2: One Pipeline to Scale Them All -- Adapting Pre-Training Data Processing to Every Language","date":"2025-06-26","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"huggingface/fineweb-2","path":"ablations/evaluation/launch_evals.py","file_url":"https://github.com/huggingface/fineweb-2/blob/HEAD/ablations/evaluation/launch_evals.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":"25e77cb73f28dda5","mcp_get_code":{"code_sha256":"25e77cb73f28dda5"}},{"arxiv_id":"2406.09072","paper":"/paper/living-in-the-moment-can-large-language","title":"Living in the Moment: Can Large Language Models Grasp Co-Temporal Reasoning?","date":"2024-06-13","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"zhaochen0110/cotempqa","path":"data_construct/facts_to_raw_data.py","file_url":"https://github.com/zhaochen0110/cotempqa/blob/HEAD/data_construct/facts_to_raw_data.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":true,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"fd241f0a32ac51bb","mcp_get_code":{"code_sha256":"fd241f0a32ac51bb"}},{"arxiv_id":"2312.01728","paper":"/paper/imputeformer-graph-transformers-for","title":"ImputeFormer: Low Rankness-Induced Transformers for Generalizable Spatiotemporal Imputation","date":"2023-12-04","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"tongnie/imputeformer","path":"experiments/imputeformer/datasets/cer_en.py","file_url":"https://github.com/tongnie/imputeformer/blob/HEAD/experiments/imputeformer/datasets/cer_en.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"d940f96a0bc64ecf","mcp_get_code":{"code_sha256":"d940f96a0bc64ecf"}},{"arxiv_id":"2306.13891","paper":"/paper/estimating-the-causal-effect-of-early","title":"Estimating the Causal Effect of Early ArXiving on Paper Acceptance","date":"2023-06-24","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"CogComp/iclr_database","path":"src/pdf_txt_parser.py","file_url":"https://github.com/CogComp/iclr_database/blob/HEAD/src/pdf_txt_parser.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"b56142048b11f367","mcp_get_code":{"code_sha256":"b56142048b11f367"}},{"arxiv_id":"2009.07365","paper":"/paper/fast-semantic-parsing-with-well-typedness","title":"Fast semantic parsing with well-typedness guarantees","date":"2020-09-15","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"Oneplus/tamr","path":"amr_aligner/system/eager/state.py","file_url":"https://github.com/Oneplus/tamr/blob/HEAD/amr_aligner/system/eager/state.py","status":"ran_draft_wrong","verification_level":1,"contract_check":"OUTPUT_MISDECLARED","metamorphic_tier":"deterministic","behaviour_fingerprint":true,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"cfb3f2e80b865160","mcp_get_code":{"code_sha256":"cfb3f2e80b865160"}}]}