{"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/eval-one-epoch","entry":"eval_one_epoch","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":2,"n_samples_fingerprinted":0,"n_places":6,"n_places_pointer_only":4,"by_status":{"ran_honours":1,"ran_violates":0,"ran_draft_wrong":1,"ran_fixture":0,"ran":0,"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":"2604.11374","paper":"/paper/arxiv-2604-11374","title":"What Do Vision-Language Models Encode for Personalized Image Aesthetics Assessment?","date":null,"month_inferred_from_arxiv_id":"2026-04","title_source":"syntology","repo":"ynklab/vlm-latent-piaa","path":"ici/phase1_train_resnet.py","file_url":"https://github.com/ynklab/vlm-latent-piaa/blob/HEAD/ici/phase1_train_resnet.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"75ca0a93cf6bb599","mcp_get_code":{"code_sha256":"75ca0a93cf6bb599"}},{"arxiv_id":"2310.19324","paper":"/paper/tempme-towards-the-explainability-of-temporal-1","title":"TempME: Towards the Explainability of Temporal Graph Neural Networks via Motif Discovery","date":"2023-10-30","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"graph-and-geometric-learning/tempme","path":"learn_base.py","file_url":"https://github.com/graph-and-geometric-learning/tempme/blob/HEAD/learn_base.py","status":"ran_draft_wrong","verification_level":1,"contract_check":"MISDECLARED","metamorphic_tier":"deterministic","behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"e7f020e7e36c8af2","mcp_get_code":{"code_sha256":"e7f020e7e36c8af2"}},{"arxiv_id":"2012.01203","paper":"/paper/learning-delaunay-surface-elements-for-mesh","title":"Learning Delaunay Surface Elements for Mesh Reconstruction","date":"2020-12-02","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"mrakotosaon/dse-meshing","path":"train_logmap/train_logmap_network.py","file_url":"https://github.com/mrakotosaon/dse-meshing/blob/HEAD/train_logmap/train_logmap_network.py","status":"ran_honours","verification_level":1,"contract_check":"HONOURS","metamorphic_tier":"well_formed","behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"d2832a2b883dabb1","mcp_get_code":{"code_sha256":"d2832a2b883dabb1"}},{"arxiv_id":"2012.01203","paper":"/paper/learning-delaunay-surface-elements-for-mesh","title":"Learning Delaunay Surface Elements for Mesh Reconstruction","date":"2020-12-02","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"mrakotosaon/dse-meshing","path":"train_logmap/train_classifier.py","file_url":"https://github.com/mrakotosaon/dse-meshing/blob/HEAD/train_logmap/train_classifier.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"05e8f1be1d6b3963","mcp_get_code":{"code_sha256":"05e8f1be1d6b3963"}},{"arxiv_id":"1901.05495","paper":"/paper/an-underwater-image-enhancement-benchmark","title":"An Underwater Image Enhancement Benchmark Dataset and Beyond","date":"2019-01-11","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"tnwei/waternet","path":"score.py","file_url":"https://github.com/tnwei/waternet/blob/HEAD/score.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"b948b1d87d466095","mcp_get_code":{"code_sha256":"b948b1d87d466095"}},{"arxiv_id":"1703.06284","paper":"/paper/multi-talker-speech-separation-with-utterance","title":"Multi-talker Speech Separation with Utterance-level Permutation Invariant Training of Deep Recurrent Neural Networks","date":"2017-03-18","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"fchest/uPIT","path":"run_lstm.py","file_url":"https://github.com/fchest/uPIT/blob/HEAD/run_lstm.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"d91435f239876721","mcp_get_code":{"code_sha256":"d91435f239876721"}}]}