{"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/cmc","entry":"cmc","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":5,"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":1,"ran_fixture":0,"ran":1,"unverified":3},"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":"2605.20735","paper":"/paper/arxiv-2605-20735","title":"Lowering the Barrier to IREX Participation: Open-Source Algorithms, Toolkit, and Benchmarking for Iris Recognition","date":null,"month_inferred_from_arxiv_id":"2026-05","title_source":"syntology","repo":"CVRL/OpenSourceIrisRecognition","path":"methods/ArcIris/Python/1N_matching.py","file_url":"https://github.com/CVRL/OpenSourceIrisRecognition/blob/HEAD/methods/ArcIris/Python/1N_matching.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"7763a16836cbc3d5","mcp_get_code":{"code_sha256":"7763a16836cbc3d5"}},{"arxiv_id":"2101.10774","paper":"/paper/lightweight-multi-branch-network-for-person","title":"Lightweight Multi-Branch Network for Person Re-Identification","date":"2021-01-26","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"jixunbo/LightMBN","path":"utils/functions.py","file_url":"https://github.com/jixunbo/LightMBN/blob/HEAD/utils/functions.py","status":"ran_draft_wrong","verification_level":1,"contract_check":"MISDECLARED","metamorphic_tier":"invariant","behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"25d4a263fb17282e","mcp_get_code":{"code_sha256":"25d4a263fb17282e"}},{"arxiv_id":"1904.02998","paper":"/paper/relation-aware-global-attention","title":"Relation-Aware Global Attention for Person Re-identification","date":"2019-04-05","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"microsoft/Relation-Aware-Global-Attention-Networks","path":"reid/evaluation_metrics/ranking.py","file_url":"https://github.com/microsoft/Relation-Aware-Global-Attention-Networks/blob/HEAD/reid/evaluation_metrics/ranking.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"b39a10404aa7ed0b","mcp_get_code":{"code_sha256":"b39a10404aa7ed0b"}},{"arxiv_id":"1904.01990","paper":"/paper/invariance-matters-exemplar-memory-for-domain","title":"Invariance Matters: Exemplar Memory for Domain Adaptive Person Re-identification","date":"2019-04-03","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"zhunzhong07/ECN","path":"reid/evaluation_metrics/ranking.py","file_url":"https://github.com/zhunzhong07/ECN/blob/HEAD/reid/evaluation_metrics/ranking.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":"b39a10404aa7ed0b","mcp_get_code":{"code_sha256":"b39a10404aa7ed0b"}},{"arxiv_id":"1804.01438","paper":"/paper/learning-discriminative-features-with","title":"Learning Discriminative Features with Multiple Granularities for Person Re-Identification","date":"2018-04-04","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"ZJULearning/PTL","path":"functions.py","file_url":"https://github.com/ZJULearning/PTL/blob/HEAD/functions.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"d829b83e56e02c65","mcp_get_code":{"code_sha256":"d829b83e56e02c65"}},{"arxiv_id":"1512.04150","paper":"/paper/learning-deep-features-for-discriminative","title":"Learning Deep Features for Discriminative Localization","date":"2015-12-14","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"HRanWang/SA","path":"reid/evaluation_metrics/ranking.py","file_url":"https://github.com/HRanWang/SA/blob/HEAD/reid/evaluation_metrics/ranking.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"45d780ae624e4a07","mcp_get_code":{"code_sha256":"45d780ae624e4a07"}}]}