{"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/load-split","entry":"load_split","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":8,"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":9,"n_samples_ran":3,"n_samples_fingerprinted":0,"n_places":9,"n_places_pointer_only":5,"by_status":{"ran_honours":0,"ran_violates":0,"ran_draft_wrong":0,"ran_fixture":0,"ran":3,"unverified":6},"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":"2607.23512","paper":"/paper/arxiv-2607-23512","title":"The Cross-Domain Generalization Cost of Offensive Language Detection","date":null,"month_inferred_from_arxiv_id":"2026-07","title_source":"syntology","repo":"renruixing/The-Cross-Domain-Generalization-Cost-of-Offensive-Language-Detection","path":"train_cascade.py","file_url":"https://github.com/renruixing/The-Cross-Domain-Generalization-Cost-of-Offensive-Language-Detection/blob/HEAD/train_cascade.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"dc67c760c61c18f2","mcp_get_code":{"code_sha256":"dc67c760c61c18f2"}},{"arxiv_id":"2606.06333","paper":"/paper/arxiv-2606-06333","title":"Subspace-Aware Sparse Autoencoders for Effective Mechanistic Interpretability","date":null,"month_inferred_from_arxiv_id":"2026-06","title_source":"syntology","repo":"arshandalili/sasa","path":"eval/absorption.py","file_url":"https://github.com/arshandalili/sasa/blob/HEAD/eval/absorption.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"2fac6816fcedb9cf","mcp_get_code":{"code_sha256":"2fac6816fcedb9cf"}},{"arxiv_id":"2604.22758","paper":"/paper/arxiv-2604-22758","title":"REDPARROT: Accelerating NL-to-DSL for Business Analytics via Query Semantic Caching","date":null,"month_inferred_from_arxiv_id":"2026-04","title_source":"syntology","repo":"TommyIsNotHere/RedParrot","path":"hybrid_rewrite/bird_rewrite.py","file_url":"https://github.com/TommyIsNotHere/RedParrot/blob/HEAD/hybrid_rewrite/bird_rewrite.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"8f99e23252478861","mcp_get_code":{"code_sha256":"8f99e23252478861"}},{"arxiv_id":"2604.22758","paper":"/paper/arxiv-2604-22758","title":"REDPARROT: Accelerating NL-to-DSL for Business Analytics via Query Semantic Caching","date":null,"month_inferred_from_arxiv_id":"2026-04","title_source":"syntology","repo":"TommyIsNotHere/RedParrot","path":"hybrid_rewrite/rewrite.py","file_url":"https://github.com/TommyIsNotHere/RedParrot/blob/HEAD/hybrid_rewrite/rewrite.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"7fc3e226730be9d1","mcp_get_code":{"code_sha256":"7fc3e226730be9d1"}},{"arxiv_id":"2603.13431","paper":"/paper/arxiv-2603-13431","title":"Chimera-Bench: A Benchmark Dataset for Epitope-Specific Antibody Design","date":null,"month_inferred_from_arxiv_id":"2026-03","title_source":"syntology","repo":"mansoor181/chimera-bench","path":"chimera_bench/data.py","file_url":"https://github.com/mansoor181/chimera-bench/blob/HEAD/chimera_bench/data.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"5f834df35bfcc4f8","mcp_get_code":{"code_sha256":"5f834df35bfcc4f8"}},{"arxiv_id":"2412.00758","paper":"/paper/3d-pdr-orion-dataset-and-neuralpdr-neural","title":"3D-PDR Orion dataset and NeuralPDR: Neural Differential Equations for Photodissociation Regions","date":"2024-12-01","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"uclchem/neuralpdr","path":"src/neuralpdr/data.py","file_url":"https://github.com/uclchem/neuralpdr/blob/HEAD/src/neuralpdr/data.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"023a2b8dac8f9b1a","mcp_get_code":{"code_sha256":"023a2b8dac8f9b1a"}},{"arxiv_id":"1811.01824","paper":"/paper/structured-neural-summarization","title":"Structured Neural Summarization","date":"2018-11-05","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"CoderPat/structured-neural-summarization","path":"parsers/naturallanguage/dmcnn/splitfiles.py","file_url":"https://github.com/CoderPat/structured-neural-summarization/blob/HEAD/parsers/naturallanguage/dmcnn/splitfiles.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"8a6a3840434a039e","mcp_get_code":{"code_sha256":"8a6a3840434a039e"}},{"arxiv_id":"1805.10915","paper":"/paper/dirichlet-based-gaussian-processes-for-large","title":"Dirichlet-based Gaussian Processes for Large-scale Calibrated Classification","date":"2018-05-28","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"dmilios/dirichletGPC","path":"src/datasets.py","file_url":"https://github.com/dmilios/dirichletGPC/blob/HEAD/src/datasets.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":"073f740b6b0dcb94","mcp_get_code":{"code_sha256":"073f740b6b0dcb94"}},{"arxiv_id":"2023.acl-long.736","paper":null,"title":"arXiv:2023.acl-long.736","date":null,"month_inferred_from_arxiv_id":null,"title_source":null,"repo":"openai/gpt-2-output-dataset","path":"baseline.py","file_url":"https://github.com/openai/gpt-2-output-dataset/blob/HEAD/baseline.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"ee362d0417f82366","mcp_get_code":{"code_sha256":"ee362d0417f82366"}}]}