{"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/f-measure","entry":"f_measure","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":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":3,"n_samples_fingerprinted":0,"n_places":6,"n_places_pointer_only":2,"by_status":{"ran_honours":0,"ran_violates":0,"ran_draft_wrong":0,"ran_fixture":0,"ran":3,"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":"2509.02807","paper":"/paper/arxiv-2509-02807","title":"PixFoundation 2.0: Do Video Multi-Modal LLMs Use Motion in Visual Grounding?","date":null,"month_inferred_from_arxiv_id":"2025-09","title_source":"syntology","repo":"MSiam/PixFoundation-2.0","path":"eval/metrics.py","file_url":"https://github.com/MSiam/PixFoundation-2.0/blob/HEAD/eval/metrics.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"0b47c87d65457a57","mcp_get_code":{"code_sha256":"0b47c87d65457a57"}},{"arxiv_id":"2406.14017","paper":"/paper/eager-two-stream-generative-recommender-with-1","title":"EAGER: Two-Stream Generative Recommender with Behavior-Semantic Collaboration","date":"2024-06-20","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"yewzz/EAGER","path":"EAGER/train_din.py","file_url":"https://github.com/yewzz/EAGER/blob/HEAD/EAGER/train_din.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"3146f2599952c1b8","mcp_get_code":{"code_sha256":"3146f2599952c1b8"}},{"arxiv_id":"2406.14017","paper":"/paper/eager-two-stream-generative-recommender-with-1","title":"EAGER: Two-Stream Generative Recommender with Behavior-Semantic Collaboration","date":"2024-06-20","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"yewzz/EAGER","path":"EAGER/train_rec.py","file_url":"https://github.com/yewzz/EAGER/blob/HEAD/EAGER/train_rec.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"626c9395b624179e","mcp_get_code":{"code_sha256":"626c9395b624179e"}},{"arxiv_id":"2312.06934","paper":"/paper/toward-real-text-manipulation-detection-new","title":"Toward Real Text Manipulation Detection: New Dataset and New Solution","date":"2023-12-12","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"drluo/rtm","path":"EvalRTM/eval_rtm.py","file_url":"https://github.com/drluo/rtm/blob/HEAD/EvalRTM/eval_rtm.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":"cc1e4f6f0f7988c2","mcp_get_code":{"code_sha256":"cc1e4f6f0f7988c2"}},{"arxiv_id":"2209.07778","paper":"/paper/spatial-then-temporal-self-supervised","title":"Spatial-then-Temporal Self-Supervised Learning for Video Correspondence","date":"2022-09-16","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"qianduoduolr/Spa-then-Temp","path":"vcl/core/evaluation/metrics.py","file_url":"https://github.com/qianduoduolr/Spa-then-Temp/blob/HEAD/vcl/core/evaluation/metrics.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"25aa01d11ecc71f5","mcp_get_code":{"code_sha256":"25aa01d11ecc71f5"}},{"arxiv_id":"2209.03138","paper":"/paper/treating-motion-as-option-to-reduce-motion","title":"Treating Motion as Option to Reduce Motion Dependency in Unsupervised Video Object Segmentation","date":"2022-09-04","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"suhwan-cho/tmo","path":"evaluation/metrics.py","file_url":"https://github.com/suhwan-cho/tmo/blob/HEAD/evaluation/metrics.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"be49186cdffed5e7","mcp_get_code":{"code_sha256":"be49186cdffed5e7"}}]}