{"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/compute-dist","entry":"compute_dist","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":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":6,"n_samples_ran":1,"n_samples_fingerprinted":0,"n_places":7,"n_places_pointer_only":2,"by_status":{"ran_honours":0,"ran_violates":0,"ran_draft_wrong":0,"ran_fixture":0,"ran":1,"unverified":5},"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":"2601.22029","paper":"/paper/arxiv-2601-22029","title":"The Ensemble Inverse Problem: Applications and Methods","date":null,"month_inferred_from_arxiv_id":"2026-01","title_source":"syntology","repo":"ZhengyanHuan/The-Ensemble-Inverse-Problem--Applications-and-Methods","path":"Sec3p2/plot_func.py","file_url":"https://github.com/ZhengyanHuan/The-Ensemble-Inverse-Problem--Applications-and-Methods/blob/HEAD/Sec3p2/plot_func.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"11fb27ffeb083e1c","mcp_get_code":{"code_sha256":"11fb27ffeb083e1c"}},{"arxiv_id":"2404.05055","paper":"/paper/percentile-criterion-optimization-in-offline-1","title":"Percentile Criterion Optimization in Offline Reinforcement Learning","date":"2024-04-07","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"elitalobo/varframework","path":"src/plot_radii.py","file_url":"https://github.com/elitalobo/varframework/blob/HEAD/src/plot_radii.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"4b7502512933d5f0","mcp_get_code":{"code_sha256":"4b7502512933d5f0"}},{"arxiv_id":"2312.10686","paper":"/paper/out-of-distribution-detection-in-long-tailed","title":"Out-of-Distribution Detection in Long-Tailed Recognition with Calibrated Outlier Class Learning","date":"2023-12-17","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"mala-lab/cocl","path":"utils/distance.py","file_url":"https://github.com/mala-lab/cocl/blob/HEAD/utils/distance.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":"7d2d217faa906bdf","mcp_get_code":{"code_sha256":"7d2d217faa906bdf"}},{"arxiv_id":"2305.05176","paper":"/paper/frugalgpt-how-to-use-large-language-models","title":"FrugalGPT: How to Use Large Language Models While Reducing Cost and Improving Performance","date":"2023-05-09","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"stanford-futuredata/frugalgpt","path":"src/FrugalGPT/optimizer.py","file_url":"https://github.com/stanford-futuredata/frugalgpt/blob/HEAD/src/FrugalGPT/optimizer.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":"afef112169d5fcf2","mcp_get_code":{"code_sha256":"afef112169d5fcf2"}},{"arxiv_id":"2204.02337","paper":"/paper/multi-scale-representation-learning-on-1","title":"Multi-Scale Representation Learning on Proteins","date":"2022-04-04","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"vsomnath/holoprot","path":"holoprot/graphs/surface.py","file_url":"https://github.com/vsomnath/holoprot/blob/HEAD/holoprot/graphs/surface.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"f97ba048177305c1","mcp_get_code":{"code_sha256":"f97ba048177305c1"}},{"arxiv_id":"1904.02113","paper":"/paper/point-cloud-oversegmentation-with-graph","title":"Point Cloud Oversegmentation with Graph-Structured Deep Metric Learning","date":"2019-04-03","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"loicland/superpoint_graph","path":"supervized_partition/losses.py","file_url":"https://github.com/loicland/superpoint_graph/blob/HEAD/supervized_partition/losses.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"2782cfa4e987b0a1","mcp_get_code":{"code_sha256":"2782cfa4e987b0a1"}},{"arxiv_id":"aaai_28217","paper":null,"title":"arXiv:aaai_28217","date":null,"month_inferred_from_arxiv_id":null,"title_source":null,"repo":"mala-lab/COCL","path":"utils/distance.py","file_url":"https://github.com/mala-lab/COCL/blob/HEAD/utils/distance.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":"7d2d217faa906bdf","mcp_get_code":{"code_sha256":"7d2d217faa906bdf"}}]}