{"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/kaiming-normal-init-weight","entry":"kaiming_normal_init_weight","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":4,"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":2,"n_samples_ran":1,"n_samples_fingerprinted":0,"n_places":5,"n_places_pointer_only":3,"by_status":{"ran_honours":0,"ran_violates":0,"ran_draft_wrong":1,"ran_fixture":0,"ran":0,"unverified":1},"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":"2402.10887","paper":"/paper/weak-mamba-unet-visual-mamba-makes-cnn-and","title":"Weak-Mamba-UNet: Visual Mamba Makes CNN and ViT Work Better for Scribble-based Medical Image Segmentation","date":"2024-02-16","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":null,"path":"","file_url":null,"status":"ran_draft_wrong","verification_level":1,"contract_check":"OUTPUT_MISDECLARED","metamorphic_tier":"deterministic","behaviour_fingerprint":false,"licence":null,"inline_ok":false,"code_sha256_prefix":"13f59065a97aef7e","mcp_get_code":{"code_sha256":"13f59065a97aef7e"}},{"arxiv_id":"2402.07245","paper":"/paper/semi-mamba-unet-pixel-level-contrastive-cross","title":"Semi-Mamba-UNet: Pixel-Level Contrastive and Pixel-Level Cross-Supervised Visual Mamba-based UNet for Semi-Supervised Medical Image Segmentation","date":"2024-02-11","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":null,"path":"","file_url":null,"status":"ran_draft_wrong","verification_level":1,"contract_check":"OUTPUT_MISDECLARED","metamorphic_tier":"deterministic","behaviour_fingerprint":false,"licence":null,"inline_ok":false,"code_sha256_prefix":"13f59065a97aef7e","mcp_get_code":{"code_sha256":"13f59065a97aef7e"}},{"arxiv_id":"2402.05079","paper":"/paper/mamba-unet-unet-like-pure-visual-mamba-for","title":"Mamba-UNet: UNet-Like Pure Visual Mamba for Medical Image Segmentation","date":"2024-02-07","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"ziyangwang007/mamba-unet","path":"code/train_Semi_Mamba_UNet.py","file_url":"https://github.com/ziyangwang007/mamba-unet/blob/HEAD/code/train_Semi_Mamba_UNet.py","status":"ran_draft_wrong","verification_level":1,"contract_check":"OUTPUT_MISDECLARED","metamorphic_tier":"deterministic","behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"code_sha256_prefix":"13f59065a97aef7e","mcp_get_code":{"code_sha256":"13f59065a97aef7e"}},{"arxiv_id":"2203.14523","paper":"/paper/translation-consistent-semi-supervised","title":"Translation Consistent Semi-supervised Segmentation for 3D Medical Images","date":"2022-03-28","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"yyliu01/tracoco","path":"Code/UnetACDC/Model/Unet2D.py","file_url":"https://github.com/yyliu01/tracoco/blob/HEAD/Code/UnetACDC/Model/Unet2D.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"25617baa9830b14c","mcp_get_code":{"code_sha256":"25617baa9830b14c"}},{"arxiv_id":"2112.04894","paper":"/paper/semi-supervised-medical-image-segmentation-2","title":"Semi-Supervised Medical Image Segmentation via Cross Teaching between CNN and Transformer","date":"2021-12-09","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":null,"path":"","file_url":null,"status":"ran_draft_wrong","verification_level":1,"contract_check":"OUTPUT_MISDECLARED","metamorphic_tier":"deterministic","behaviour_fingerprint":false,"licence":null,"inline_ok":false,"code_sha256_prefix":"13f59065a97aef7e","mcp_get_code":{"code_sha256":"13f59065a97aef7e"}}]}