{"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/aggregate-similarity","entry":"aggregate_similarity","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":4,"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":3,"n_samples_ran":2,"n_samples_fingerprinted":0,"n_places":5,"n_places_pointer_only":3,"by_status":{"ran_honours":0,"ran_violates":0,"ran_draft_wrong":0,"ran_fixture":2,"ran":0,"unverified":1},"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":"2602.21492","paper":"/paper/arxiv-2602-21492","title":"GradAlign: Gradient-Aligned Data Selection for LLM Reinforcement Learning","date":null,"month_inferred_from_arxiv_id":"2026-02","title_source":"syntology","repo":"StigLidu/GradAlign","path":"automated/aggregate.py","file_url":"https://github.com/StigLidu/GradAlign/blob/HEAD/automated/aggregate.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"f8d2cea71368ec06","mcp_get_code":{"code_sha256":"f8d2cea71368ec06"}},{"arxiv_id":"2504.20860","paper":null,"title":"arXiv:2504.20860","date":null,"month_inferred_from_arxiv_id":"2025-04","title_source":null,"repo":null,"path":"","file_url":null,"status":"ran_fixture","verification_level":1,"contract_check":"RAISES","metamorphic_tier":"invariant","behaviour_fingerprint":false,"licence":null,"inline_ok":false,"code_sha256_prefix":"3936ee935ec8fce1","mcp_get_code":{"code_sha256":"3936ee935ec8fce1"}},{"arxiv_id":"2407.14412","paper":"/paper/deal-disentangle-and-localize-concept-level","title":"DEAL: Disentangle and Localize Concept-level Explanations for VLMs","date":"2024-07-19","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"tangli-udel/DEAL","path":"load.py","file_url":"https://github.com/tangli-udel/DEAL/blob/HEAD/load.py","status":"ran_fixture","verification_level":1,"contract_check":"RAISES","metamorphic_tier":"invariant","behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"3936ee935ec8fce1","mcp_get_code":{"code_sha256":"3936ee935ec8fce1"}},{"arxiv_id":"2306.07282","paper":"/paper/waffling-around-for-performance-visual","title":"Waffling around for Performance: Visual Classification with Random Words and Broad Concepts","date":"2023-06-12","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"hk1ee/comparative-clip","path":"src/tools.py","file_url":"https://github.com/hk1ee/comparative-clip/blob/HEAD/src/tools.py","status":"ran_fixture","verification_level":1,"contract_check":"RAISES","metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"5fde11e2c3b80a04","mcp_get_code":{"code_sha256":"5fde11e2c3b80a04"}},{"arxiv_id":"2210.07183","paper":"/paper/visual-classification-via-description-from","title":"Visual Classification via Description from Large Language Models","date":"2022-10-13","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"sachit-menon/classify_by_description_release","path":"load.py","file_url":"https://github.com/sachit-menon/classify_by_description_release/blob/HEAD/load.py","status":"ran_fixture","verification_level":1,"contract_check":"RAISES","metamorphic_tier":"invariant","behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"3936ee935ec8fce1","mcp_get_code":{"code_sha256":"3936ee935ec8fce1"}}]}