{"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/get-model-family","entry":"get_model_family","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":6,"n_papers_ran":2,"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":6,"n_samples_ran":2,"n_samples_fingerprinted":0,"n_places":6,"n_places_pointer_only":1,"by_status":{"ran_honours":0,"ran_violates":0,"ran_draft_wrong":0,"ran_fixture":0,"ran":2,"unverified":4},"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":"2607.19317","paper":"/paper/arxiv-2607-19317","title":"Circuit Discovery, Evaluation, and Application Toolkit for Mechanistic Interpretability","date":null,"month_inferred_from_arxiv_id":"2026-07","title_source":"syntology","repo":"Lexsi-Labs/CircuitKIT","path":"src/circuitkit/applications/arch_registry.py","file_url":"https://github.com/Lexsi-Labs/CircuitKIT/blob/HEAD/src/circuitkit/applications/arch_registry.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NOASSERTION","inline_ok":false,"code_sha256_prefix":"202a8ec5c82de84c","mcp_get_code":{"code_sha256":"202a8ec5c82de84c"}},{"arxiv_id":"2405.20947","paper":"/paper/or-bench-an-over-refusal-benchmark-for-large","title":"OR-Bench: An Over-Refusal Benchmark for Large Language Models","date":"2024-05-31","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"justincui03/or-bench","path":"plot.py","file_url":"https://github.com/justincui03/or-bench/blob/HEAD/plot.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":"8c4e4c1d7c7dd67d","mcp_get_code":{"code_sha256":"8c4e4c1d7c7dd67d"}},{"arxiv_id":"2405.10938","paper":"/paper/observational-scaling-laws-and-the","title":"Observational Scaling Laws and the Predictability of Language Model Performance","date":"2024-05-17","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"ryoungj/ObsScaling","path":"utils/selection.py","file_url":"https://github.com/ryoungj/ObsScaling/blob/HEAD/utils/selection.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"code_sha256_prefix":"be5e108bf6b36aa5","mcp_get_code":{"code_sha256":"be5e108bf6b36aa5"}},{"arxiv_id":"2310.02207","paper":"/paper/language-models-represent-space-and-time","title":"Language Models Represent Space and Time","date":"2023-10-03","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"wesg52/world-models","path":"utils.py","file_url":"https://github.com/wesg52/world-models/blob/HEAD/utils.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"9931b4001e67bb95","mcp_get_code":{"code_sha256":"9931b4001e67bb95"}},{"arxiv_id":"2305.09731","paper":"/paper/what-in-context-learning-learns-in-context","title":"What In-Context Learning \"Learns\" In-Context: Disentangling Task Recognition and Task Learning","date":"2023-05-16","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"princeton-nlp/whaticllearns","path":"spb/compute_summary_stats.py","file_url":"https://github.com/princeton-nlp/whaticllearns/blob/HEAD/spb/compute_summary_stats.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"2cc275485c860a52","mcp_get_code":{"code_sha256":"2cc275485c860a52"}},{"arxiv_id":"2211.01834","paper":"/paper/toward-unsupervised-outlier-model-selection","title":"Toward Unsupervised Outlier Model Selection","date":"2022-11-03","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"yzhao062/elect","path":"utility.py","file_url":"https://github.com/yzhao062/elect/blob/HEAD/utility.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"BSD-2-Clause","inline_ok":true,"code_sha256_prefix":"ee8efc17fd683c52","mcp_get_code":{"code_sha256":"ee8efc17fd683c52"}}]}