{"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/load-eval-data","entry":"load_eval_data","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":7,"n_papers_ran":1,"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":7,"n_samples_ran":1,"n_samples_fingerprinted":0,"n_places":7,"n_places_pointer_only":1,"by_status":{"ran_honours":0,"ran_violates":0,"ran_draft_wrong":0,"ran_fixture":0,"ran":1,"unverified":6},"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":"2404.18988","paper":"/paper/markovian-agents-for-truthful-language","title":"Markovian Transformers for Informative Language Modeling","date":"2024-04-29","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"scottviteri/MarkovianTraining","path":"src/plot_alignment_scatter.py","file_url":"https://github.com/scottviteri/MarkovianTraining/blob/HEAD/src/plot_alignment_scatter.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"360a656c320a63f7","mcp_get_code":{"code_sha256":"360a656c320a63f7"}},{"arxiv_id":"2402.05457","paper":"/paper/it-s-never-too-late-fusing-acoustic","title":"It's Never Too Late: Fusing Acoustic Information into Large Language Models for Automatic Speech Recognition","date":"2024-02-08","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"Hypotheses-Paradise/UADF","path":"evaluate/adapter.py","file_url":"https://github.com/Hypotheses-Paradise/UADF/blob/HEAD/evaluate/adapter.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"code_sha256_prefix":"854aeb584ed6b2b0","mcp_get_code":{"code_sha256":"854aeb584ed6b2b0"}},{"arxiv_id":"2304.14329","paper":"/paper/learning-to-extrapolate-a-transductive","title":"Learning to Extrapolate: A Transductive Approach","date":"2023-04-27","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"learningmatter-mit/matex","path":"blt/plot_maker/plots.py","file_url":"https://github.com/learningmatter-mit/matex/blob/HEAD/blt/plot_maker/plots.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"842c29ed353636df","mcp_get_code":{"code_sha256":"842c29ed353636df"}},{"arxiv_id":"2304.03728","paper":"/paper/interpretable-unified-language-checking","title":"Interpretable Unified Language Checking","date":"2023-04-07","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"luohongyin/unilc","path":"analysis.py","file_url":"https://github.com/luohongyin/unilc/blob/HEAD/analysis.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"3c472e1547a3c5cb","mcp_get_code":{"code_sha256":"3c472e1547a3c5cb"}},{"arxiv_id":"2204.06252","paper":"/paper/what-matters-in-language-conditioned-robotic","title":"What Matters in Language Conditioned Robotic Imitation Learning over Unstructured Data","date":"2022-04-13","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"lukashermann/hulc","path":"hulc/evaluation/create_plots.py","file_url":"https://github.com/lukashermann/hulc/blob/HEAD/hulc/evaluation/create_plots.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"1dfe6f74142d8825","mcp_get_code":{"code_sha256":"1dfe6f74142d8825"}},{"arxiv_id":"1310.4546","paper":"/paper/distributed-representations-of-words-and-1","title":"Distributed Representations of Words and Phrases and their Compositionality","date":"2013-10-16","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"JoegameZhou/ms-skipgram","path":"infer/sdk/infer_eval.py","file_url":"https://github.com/JoegameZhou/ms-skipgram/blob/HEAD/infer/sdk/infer_eval.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"code_sha256_prefix":"a17c8357ae091ec8","mcp_get_code":{"code_sha256":"a17c8357ae091ec8"}},{"arxiv_id":"2024.findings-emnlp.504","paper":null,"title":"arXiv:2024.findings-emnlp.504","date":null,"month_inferred_from_arxiv_id":null,"title_source":null,"repo":"Re-Align/URIAL","path":"src/legacy/vllm_infer/vllm_urial.py","file_url":"https://github.com/Re-Align/URIAL/blob/HEAD/src/legacy/vllm_infer/vllm_urial.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"code_sha256_prefix":"5307f9cdcc42a778","mcp_get_code":{"code_sha256":"5307f9cdcc42a778"}}]}