{"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/patching","entry":"patching","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":7,"n_papers_ran":5,"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":2,"n_samples_fingerprinted":0,"n_places":8,"n_places_pointer_only":5,"by_status":{"ran_honours":0,"ran_violates":0,"ran_draft_wrong":1,"ran_fixture":0,"ran":1,"unverified":3},"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":"2605.17730","paper":"/paper/arxiv-2605-17730","title":"L-Drive: Beyond a Single Mapping-Latent Context Drives Time Series Forecasting","date":null,"month_inferred_from_arxiv_id":"2026-05","title_source":"syntology","repo":"ShijunChen01/L-Drive","path":"models/L_Drive.py","file_url":"https://github.com/ShijunChen01/L-Drive/blob/HEAD/models/L_Drive.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"250adad55c18ec57","mcp_get_code":{"code_sha256":"250adad55c18ec57"}},{"arxiv_id":"2602.01951","paper":"/paper/arxiv-2602-01951","title":"Enabling Progressive Whole-slide Image Analysis with Multi-scale Pyramidal Network","date":null,"month_inferred_from_arxiv_id":"2026-02","title_source":"syntology","repo":"CraigMyles/SurGen-Dataset","path":"reproducibility/create_patches.py","file_url":"https://github.com/CraigMyles/SurGen-Dataset/blob/HEAD/reproducibility/create_patches.py","status":"ran_draft_wrong","verification_level":1,"contract_check":"OUTPUT_MISDECLARED","metamorphic_tier":"none","behaviour_fingerprint":false,"licence":"GPL-3.0","inline_ok":false,"code_sha256_prefix":"6ca1f4cd53ffd7e6","mcp_get_code":{"code_sha256":"6ca1f4cd53ffd7e6"}},{"arxiv_id":"2602.01951","paper":"/paper/arxiv-2602-01951","title":"Enabling Progressive Whole-slide Image Analysis with Multi-scale Pyramidal Network","date":null,"month_inferred_from_arxiv_id":"2026-02","title_source":"syntology","repo":"mahmoodlab/CLAM","path":"create_patches.py","file_url":"https://github.com/mahmoodlab/CLAM/blob/HEAD/create_patches.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"GPL-3.0","inline_ok":false,"code_sha256_prefix":"1f0265b494709bf9","mcp_get_code":{"code_sha256":"1f0265b494709bf9"}},{"arxiv_id":"2505.17982","paper":null,"title":"arXiv:2505.17982","date":null,"month_inferred_from_arxiv_id":"2025-05","title_source":null,"repo":"bryanwong17/HiVE-MIL","path":"create_patches_fp.py","file_url":"https://github.com/bryanwong17/HiVE-MIL/blob/HEAD/create_patches_fp.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"88d96f0bf9d56484","mcp_get_code":{"code_sha256":"88d96f0bf9d56484"}},{"arxiv_id":"2406.15303","paper":"/paper/adr-attention-diversification-regularization","title":"AEM: Attention Entropy Maximization for Multiple Instance Learning based Whole Slide Image Classification","date":"2024-06-18","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"dazhangyu123/adr","path":"Step1_create_patches_fp.py","file_url":"https://github.com/dazhangyu123/adr/blob/HEAD/Step1_create_patches_fp.py","status":"ran_draft_wrong","verification_level":1,"contract_check":"OUTPUT_MISDECLARED","metamorphic_tier":"none","behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"6ca1f4cd53ffd7e6","mcp_get_code":{"code_sha256":"6ca1f4cd53ffd7e6"}},{"arxiv_id":"2404.13222","paper":"/paper/vim4path-self-supervised-vision-mamba-for","title":"Vim4Path: Self-Supervised Vision Mamba for Histopathology Images","date":"2024-04-20","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":"none","behaviour_fingerprint":false,"licence":null,"inline_ok":false,"code_sha256_prefix":"6ca1f4cd53ffd7e6","mcp_get_code":{"code_sha256":"6ca1f4cd53ffd7e6"}},{"arxiv_id":"2311.07125","paper":"/paper/attention-challenging-multiple-instance","title":"Attention-Challenging Multiple Instance Learning for Whole Slide Image Classification","date":"2023-11-13","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"dazhangyu123/acmil","path":"Step1_create_patches_fp.py","file_url":"https://github.com/dazhangyu123/acmil/blob/HEAD/Step1_create_patches_fp.py","status":"ran_draft_wrong","verification_level":1,"contract_check":"OUTPUT_MISDECLARED","metamorphic_tier":"none","behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"6ca1f4cd53ffd7e6","mcp_get_code":{"code_sha256":"6ca1f4cd53ffd7e6"}},{"arxiv_id":"2024.findings-emnlp.815","paper":null,"title":"arXiv:2024.findings-emnlp.815","date":null,"month_inferred_from_arxiv_id":null,"title_source":null,"repo":"behavioral-data/BLADE","path":"blade_bench/logger.py","file_url":"https://github.com/behavioral-data/BLADE/blob/HEAD/blade_bench/logger.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":"08309d2e1e9e1402","mcp_get_code":{"code_sha256":"08309d2e1e9e1402"}}]}