{"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-dist-info","entry":"get_dist_info","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":2,"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":4,"n_samples_ran":2,"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":2,"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":"2501.15510","paper":"/paper/universal-image-restoration-pre-training-via","title":"Universal Image Restoration Pre-training via Degradation Classification","date":"2025-01-26","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"milab-pku/dcpt","path":"basicsr/models/degradation_classification_pretrain_model.py","file_url":"https://github.com/milab-pku/dcpt/blob/HEAD/basicsr/models/degradation_classification_pretrain_model.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":"well_formed","behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"34c62f60981f053e","mcp_get_code":{"code_sha256":"34c62f60981f053e"}},{"arxiv_id":"2404.03635","paper":"/paper/wordepth-variational-language-prior-for","title":"WorDepth: Variational Language Prior for Monocular Depth Estimation","date":"2024-04-04","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"Adonis-galaxy/WorDepth","path":"src/networks/wordepth.py","file_url":"https://github.com/Adonis-galaxy/WorDepth/blob/HEAD/src/networks/wordepth.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":"well_formed","behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"a91567db5e6c35b4","mcp_get_code":{"code_sha256":"a91567db5e6c35b4"}},{"arxiv_id":"2312.09243","paper":"/paper/occnerf-self-supervised-multi-camera","title":"OccNeRF: Advancing 3D Occupancy Prediction in LiDAR-Free Environments","date":"2023-12-14","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"linshan-bin/occnerf","path":"run_vis.py","file_url":"https://github.com/linshan-bin/occnerf/blob/HEAD/run_vis.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":"b88b70494e7decdc","mcp_get_code":{"code_sha256":"b88b70494e7decdc"}},{"arxiv_id":"2204.03636","paper":"/paper/surrounddepth-entangling-surrounding-views","title":"SurroundDepth: Entangling Surrounding Views for Self-Supervised Multi-Camera Depth Estimation","date":"2022-04-07","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"weiyithu/surrounddepth","path":"runer.py","file_url":"https://github.com/weiyithu/surrounddepth/blob/HEAD/runer.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"59c37841287955b4","mcp_get_code":{"code_sha256":"59c37841287955b4"}},{"arxiv_id":"Gan_GaussianOcc_Fully_Self-supervised_and_Efficient_3D_Occupancy_Estimation_with_Gaussian_ICCV_2025_paper","paper":null,"title":"arXiv:Gan_GaussianOcc_Fully_Self-supervised_and_Efficient_3D_Occupancy_Estimation_with_Gaussian_ICCV_2025_paper","date":null,"month_inferred_from_arxiv_id":null,"title_source":null,"repo":"GANWANSHUI/GaussianOcc","path":"run_vis.py","file_url":"https://github.com/GANWANSHUI/GaussianOcc/blob/HEAD/run_vis.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":"b88b70494e7decdc","mcp_get_code":{"code_sha256":"b88b70494e7decdc"}}]}