{"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/get-precomp-loader","entry":"get_precomp_loader","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":1,"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":1,"n_samples_fingerprinted":0,"n_places":5,"n_places_pointer_only":1,"by_status":{"ran_honours":0,"ran_violates":0,"ran_draft_wrong":0,"ran_fixture":0,"ran":1,"unverified":4},"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":"2502.19128","paper":"/paper/sca3d-enhancing-cross-modal-3d-retrieval-via","title":"SCA3D: Enhancing Cross-modal 3D Retrieval via 3D Shape and Caption Paired Data Augmentation","date":"2025-02-26","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"3dagentworld/sca3d","path":"SCA3D/dataloaders/data.py","file_url":"https://github.com/3dagentworld/sca3d/blob/HEAD/SCA3D/dataloaders/data.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"9a65548557b55500","mcp_get_code":{"code_sha256":"9a65548557b55500"}},{"arxiv_id":"2310.17468","paper":"/paper/cross-modal-active-complementary-learning-1","title":"Cross-modal Active Complementary Learning with Self-refining Correspondence","date":"2023-10-26","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"QinYang79/CRCL","path":"CRCL_NeurIPS23/data.py","file_url":"https://github.com/QinYang79/CRCL/blob/HEAD/CRCL_NeurIPS23/data.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"091fa44320344aae","mcp_get_code":{"code_sha256":"091fa44320344aae"}},{"arxiv_id":"2107.01872","paper":"/paper/part2word-learning-joint-embedding-of-point","title":"Parts2Words: Learning Joint Embedding of Point Clouds and Texts by Bidirectional Matching between Parts and Words","date":"2021-07-05","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"jlutangchuan/parts2words","path":"parts2words/dataloaders/data.py","file_url":"https://github.com/jlutangchuan/parts2words/blob/HEAD/parts2words/dataloaders/data.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"a7c37b3d1620a9b8","mcp_get_code":{"code_sha256":"a7c37b3d1620a9b8"}},{"arxiv_id":"2010.03403","paper":"/paper/universal-weighting-metric-learning-for-cross-1","title":"Universal Weighting Metric Learning for Cross-Modal Matching","date":"2020-10-07","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"wayne980/PolyLoss","path":"data.py","file_url":"https://github.com/wayne980/PolyLoss/blob/HEAD/data.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":"329698e5a722c7d4","mcp_get_code":{"code_sha256":"329698e5a722c7d4"}},{"arxiv_id":"1803.08024","paper":"/paper/stacked-cross-attention-for-image-text","title":"Stacked Cross Attention for Image-Text Matching","date":"2018-03-21","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"idejie/SCAN","path":"data.py","file_url":"https://github.com/idejie/SCAN/blob/HEAD/data.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":"f8b728dce3e79700","mcp_get_code":{"code_sha256":"f8b728dce3e79700"}}]}