{"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/onehot-encoding","entry":"onehot_encoding","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":3,"n_samples_ran":2,"n_samples_fingerprinted":1,"n_places":5,"n_places_pointer_only":2,"by_status":{"ran_honours":0,"ran_violates":0,"ran_draft_wrong":1,"ran_fixture":0,"ran":1,"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":"2402.11168","paper":"/paper/trust-regions-for-explanations-via-black-box","title":"Trust Regions for Explanations via Black-Box Probabilistic Certification","date":"2024-02-17","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"Trusted-AI/AIX360","path":"aix360/algorithms/cofrnet/utils.py","file_url":"https://github.com/Trusted-AI/AIX360/blob/HEAD/aix360/algorithms/cofrnet/utils.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"code_sha256_prefix":"d269f5f6d592112e","mcp_get_code":{"code_sha256":"d269f5f6d592112e"}},{"arxiv_id":"2307.00631","paper":"/paper/bidirectional-looking-with-a-novel-double","title":"Bidirectional Looking with A Novel Double Exponential Moving Average to Adaptive and Non-adaptive Momentum Optimizers","date":"2023-07-02","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"chernyn/admeta-optimizer","path":"admeta-code/admeta-cifar/pytorch_image_classification/losses/label_smoothing.py","file_url":"https://github.com/chernyn/admeta-optimizer/blob/HEAD/admeta-code/admeta-cifar/pytorch_image_classification/losses/label_smoothing.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"BSD-2-Clause","inline_ok":true,"code_sha256_prefix":"fc5b24dc25537ab8","mcp_get_code":{"code_sha256":"fc5b24dc25537ab8"}},{"arxiv_id":"2211.15656","paper":"/paper/superfusion-multilevel-lidar-camera-fusion","title":"SuperFusion: Multilevel LiDAR-Camera Fusion for Long-Range HD Map Generation","date":"2022-11-28","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":null,"path":"","file_url":null,"status":"ran_draft_wrong","verification_level":1,"contract_check":"MISDECLARED","metamorphic_tier":"invariant","behaviour_fingerprint":true,"licence":null,"inline_ok":false,"code_sha256_prefix":"7ab535c06ef669db","mcp_get_code":{"code_sha256":"7ab535c06ef669db"}},{"arxiv_id":"2107.06307","paper":"/paper/hdmapnet-an-online-hd-map-construction-and","title":"HDMapNet: An Online HD Map Construction and Evaluation Framework","date":"2021-07-13","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"Tsinghua-MARS-Lab/HDMapNet","path":"evaluate.py","file_url":"https://github.com/Tsinghua-MARS-Lab/HDMapNet/blob/HEAD/evaluate.py","status":"ran_draft_wrong","verification_level":1,"contract_check":"MISDECLARED","metamorphic_tier":"invariant","behaviour_fingerprint":true,"licence":"GPL-3.0","inline_ok":false,"code_sha256_prefix":"7ab535c06ef669db","mcp_get_code":{"code_sha256":"7ab535c06ef669db"}},{"arxiv_id":"1909.03012","paper":"/paper/one-explanation-does-not-fit-all-a-toolkit","title":"One Explanation Does Not Fit All: A Toolkit and Taxonomy of AI Explainability Techniques","date":"2019-09-06","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"IBM/AIX360","path":"aix360/algorithms/cofrnet/utils.py","file_url":"https://github.com/IBM/AIX360/blob/HEAD/aix360/algorithms/cofrnet/utils.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"code_sha256_prefix":"d269f5f6d592112e","mcp_get_code":{"code_sha256":"d269f5f6d592112e"}}]}