{"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/matrix-diag","entry":"matrix_diag","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":3,"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":1,"n_samples_fingerprinted":1,"n_places":6,"n_places_pointer_only":3,"by_status":{"ran_honours":0,"ran_violates":0,"ran_draft_wrong":1,"ran_fixture":0,"ran":0,"unverified":2},"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":"2602.03024","paper":"/paper/arxiv-2602-03024","title":"Consistency Deep Equilibrium Models","date":null,"month_inferred_from_arxiv_id":"2026-02","title_source":"syntology","repo":"landrarwolf/CDEQ","path":"CDEQ-src/lib/optimizations.py","file_url":"https://github.com/landrarwolf/CDEQ/blob/HEAD/CDEQ-src/lib/optimizations.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"f06524d1a24b825a","mcp_get_code":{"code_sha256":"f06524d1a24b825a"}},{"arxiv_id":"2501.01108","paper":"/paper/muq-self-supervised-music-representation","title":"MuQ: Self-Supervised Music Representation Learning with Mel Residual Vector Quantization","date":"2025-01-02","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"tencent-ailab/muq","path":"src/muq/muq_mulan/modules/contrastive.py","file_url":"https://github.com/tencent-ailab/muq/blob/HEAD/src/muq/muq_mulan/modules/contrastive.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":false,"code_sha256_prefix":"d52bf6e1f34bb253","mcp_get_code":{"code_sha256":"d52bf6e1f34bb253"}},{"arxiv_id":"2411.00899","paper":"/paper/certified-robustness-for-deep-equilibrium-1","title":"Certified Robustness for Deep Equilibrium Models via Serialized Random Smoothing","date":"2024-11-01","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"WeizhiGao/Serialized-Randomized-Smoothing","path":"DEQ/lib/optimizations.py","file_url":"https://github.com/WeizhiGao/Serialized-Randomized-Smoothing/blob/HEAD/DEQ/lib/optimizations.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"f06524d1a24b825a","mcp_get_code":{"code_sha256":"f06524d1a24b825a"}},{"arxiv_id":"2301.10677","paper":"/paper/imitating-human-behaviour-with-diffusion","title":"Imitating Human Behaviour with Diffusion Models","date":"2023-01-25","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"microsoft/imitating-human-behaviour-w-diffusion","path":"code/models.py","file_url":"https://github.com/microsoft/imitating-human-behaviour-w-diffusion/blob/HEAD/code/models.py","status":"ran_draft_wrong","verification_level":1,"contract_check":"MISDECLARED","metamorphic_tier":null,"behaviour_fingerprint":true,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"f29345568db89515","mcp_get_code":{"code_sha256":"f29345568db89515"}},{"arxiv_id":"2204.13846","paper":"/paper/rosa-a-robust-self-aligned-framework-for-node","title":"RoSA: A Robust Self-Aligned Framework for Node-Node Graph Contrastive Learning","date":"2022-04-29","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"ZhuYun97/RoSA","path":"model.py","file_url":"https://github.com/ZhuYun97/RoSA/blob/HEAD/model.py","status":"ran_draft_wrong","verification_level":1,"contract_check":"MISDECLARED","metamorphic_tier":null,"behaviour_fingerprint":true,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"f29345568db89515","mcp_get_code":{"code_sha256":"f29345568db89515"}},{"arxiv_id":"2106.03375","paper":"/paper/commutative-lie-group-vae-for-disentanglement","title":"Commutative Lie Group VAE for Disentanglement Learning","date":"2021-06-07","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"zhuxinqimac/CommutativeLieGroupVAE-Pytorch","path":"models/dip_vae.py","file_url":"https://github.com/zhuxinqimac/CommutativeLieGroupVAE-Pytorch/blob/HEAD/models/dip_vae.py","status":"ran_draft_wrong","verification_level":1,"contract_check":"MISDECLARED","metamorphic_tier":null,"behaviour_fingerprint":true,"licence":"Apache-2.0","inline_ok":true,"code_sha256_prefix":"f29345568db89515","mcp_get_code":{"code_sha256":"f29345568db89515"}}]}