{"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/visionrotaryembeddingfast","entry":"VisionRotaryEmbeddingFast","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":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":5,"n_samples_ran":3,"n_samples_fingerprinted":0,"n_places":5,"n_places_pointer_only":2,"by_status":{"ran_honours":0,"ran_violates":0,"ran_draft_wrong":0,"ran_fixture":0,"ran":3,"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":"2607.12753","paper":"/paper/arxiv-2607-12753","title":"RFMSR: Residual Flow Matching for Image Super-Resolution","date":null,"month_inferred_from_arxiv_id":"2026-07","title_source":"syntology","repo":"Faze-Hsw/RFMSR","path":"models/rfmsr.py","file_url":"https://github.com/Faze-Hsw/RFMSR/blob/HEAD/models/rfmsr.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"ee479f4bf25b2922","mcp_get_code":{"code_sha256":"ee479f4bf25b2922"}},{"arxiv_id":"2603.14366","paper":"/paper/arxiv-2603-14366","title":"Representation Alignment for Just Image Transformers is not Easier than You Think","date":null,"month_inferred_from_arxiv_id":"2026-03","title_source":"syntology","repo":"kaist-cvml/PixelREPA","path":"model_pixelREPA.py","file_url":"https://github.com/kaist-cvml/PixelREPA/blob/HEAD/model_pixelREPA.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"38af29b14f134328","mcp_get_code":{"code_sha256":"38af29b14f134328"}},{"arxiv_id":"2602.02493","paper":"/paper/arxiv-2602-02493","title":"PixelGen: Improving Pixel Diffusion with Perceptual Supervision","date":null,"month_inferred_from_arxiv_id":"2026-02","title_source":"syntology","repo":"Zehong-Ma/PixelGen","path":"src/models/transformer/JiT.py","file_url":"https://github.com/Zehong-Ma/PixelGen/blob/HEAD/src/models/transformer/JiT.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"658e3e322c0668b6","mcp_get_code":{"code_sha256":"658e3e322c0668b6"}},{"arxiv_id":"2602.02156","paper":"/paper/arxiv-2602-02156","title":"LoopViT: Scaling Visual ARC with Looped Transformers","date":null,"month_inferred_from_arxiv_id":"2026-02","title_source":"syntology","repo":"WenjieShu/LoopViT","path":"src/ARC_LoopViT.py","file_url":"https://github.com/WenjieShu/LoopViT/blob/HEAD/src/ARC_LoopViT.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"87498b7d77eb0943","mcp_get_code":{"code_sha256":"87498b7d77eb0943"}},{"arxiv_id":"2410.10356","paper":"/paper/fasterdit-towards-faster-diffusion","title":"FasterDiT: Towards Faster Diffusion Transformers Training without Architecture Modification","date":"2024-10-14","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"hustvl/LightningDiT","path":"models/lightningdit.py","file_url":"https://github.com/hustvl/LightningDiT/blob/HEAD/models/lightningdit.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"64a16f9548e5d293","mcp_get_code":{"code_sha256":"64a16f9548e5d293"}}]}