{"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/flash-attention","entry":"flash_attention","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":8,"n_papers_ran":0,"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":0,"n_samples_fingerprinted":0,"n_places":8,"n_places_pointer_only":2,"by_status":{"ran_honours":0,"ran_violates":0,"ran_draft_wrong":0,"ran_fixture":0,"ran":0,"unverified":5},"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":"2604.18215","paper":"/paper/arxiv-2604-18215","title":"Memorize When Needed: Decoupled Memory Control for Spatially Consistent Long-Horizon Video Generation","date":null,"month_inferred_from_arxiv_id":"2026-04","title_source":"syntology","repo":"iguoyanjun/Memorize-When-Needed","path":"models/wan_modules/attention_utils.py","file_url":"https://github.com/iguoyanjun/Memorize-When-Needed/blob/HEAD/models/wan_modules/attention_utils.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"7ea44a4680b76539","mcp_get_code":{"code_sha256":"7ea44a4680b76539"}},{"arxiv_id":"2602.15922","paper":"/paper/arxiv-2602-15922","title":"World Action Models are Zero-shot Policies","date":"2026-02-17","month_inferred_from_arxiv_id":null,"title_source":"syntology","repo":"dreamzero0/dreamzero","path":"groot/vla/model/dreamzero/modules/attention.py","file_url":"https://github.com/dreamzero0/dreamzero/blob/HEAD/groot/vla/model/dreamzero/modules/attention.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":"5f985627e201aeeb","mcp_get_code":{"code_sha256":"5f985627e201aeeb"}},{"arxiv_id":"2507.06119","paper":"/paper/omni-video-democratizing-unified-video","title":"Omni-Video: Democratizing Unified Video Understanding and Generation","date":"2025-07-08","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"sais-fuxi/omni-video","path":"omnivideo/modules/attention.py","file_url":"https://github.com/sais-fuxi/omni-video/blob/HEAD/omnivideo/modules/attention.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"c2098ac910a95bc5","mcp_get_code":{"code_sha256":"c2098ac910a95bc5"}},{"arxiv_id":"2505.23742","paper":"/paper/magref-masked-guidance-for-any-reference","title":"MAGREF: Masked Guidance for Any-Reference Video Generation","date":"2025-05-29","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"magref-video/magref","path":"magref/modules/attention.py","file_url":"https://github.com/magref-video/magref/blob/HEAD/magref/modules/attention.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":"7ea44a4680b76539","mcp_get_code":{"code_sha256":"7ea44a4680b76539"}},{"arxiv_id":"2505.21136","paper":"/paper/sageattention2-a-more-efficient","title":"SageAttention2++: A More Efficient Implementation of SageAttention2","date":"2025-05-27","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"thu-ml/spargeattn","path":"evaluate/modify_model/modify_wan.py","file_url":"https://github.com/thu-ml/spargeattn/blob/HEAD/evaluate/modify_model/modify_wan.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":"981589653d7e97ee","mcp_get_code":{"code_sha256":"981589653d7e97ee"}},{"arxiv_id":"2503.07598","paper":"/paper/vace-all-in-one-video-creation-and-editing","title":"VACE: All-in-One Video Creation and Editing","date":"2025-03-10","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"wan-video/wan2.1","path":"wan/modules/vace_model.py","file_url":"https://github.com/wan-video/wan2.1/blob/HEAD/wan/modules/vace_model.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":"7ea44a4680b76539","mcp_get_code":{"code_sha256":"7ea44a4680b76539"}},{"arxiv_id":"2502.11079","paper":"/paper/phantom-subject-consistent-video-generation","title":"Phantom: Subject-consistent video generation via cross-modal alignment","date":"2025-02-16","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"phantom-video/phantom","path":"phantom_wan/modules/attention.py","file_url":"https://github.com/phantom-video/phantom/blob/HEAD/phantom_wan/modules/attention.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":"7ea44a4680b76539","mcp_get_code":{"code_sha256":"7ea44a4680b76539"}},{"arxiv_id":"2312.00407","paper":"/paper/collie-collaborative-training-of-large","title":"CoLLiE: Collaborative Training of Large Language Models in an Efficient Way","date":"2023-12-01","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"OpenLMLab/collie","path":"collie/models/utils.py","file_url":"https://github.com/OpenLMLab/collie/blob/HEAD/collie/models/utils.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":"f854c14e7ec1871d","mcp_get_code":{"code_sha256":"f854c14e7ec1871d"}}]}