{"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/parse-meta","entry":"parse_meta","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":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":4,"n_samples_ran":1,"n_samples_fingerprinted":1,"n_places":7,"n_places_pointer_only":1,"by_status":{"ran_honours":0,"ran_violates":0,"ran_draft_wrong":1,"ran_fixture":0,"ran":0,"unverified":3},"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":"2604.25057","paper":"/paper/arxiv-2604-25057","title":"CiteRadar: A Citation Intelligence Platform for Researcher Profiling and Geographic Visualization","date":null,"month_inferred_from_arxiv_id":"2026-04","title_source":"syntology","repo":"chenxuniu/citeradar","path":"citeradar/tracker.py","file_url":"https://github.com/chenxuniu/citeradar/blob/HEAD/citeradar/tracker.py","status":"ran_draft_wrong","verification_level":1,"contract_check":"OUTPUT_MISDECLARED","metamorphic_tier":"deterministic","behaviour_fingerprint":true,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"4f0de2d8b69abb7a","mcp_get_code":{"code_sha256":"4f0de2d8b69abb7a"}},{"arxiv_id":"2603.17685","paper":"/paper/arxiv-2603-17685","title":"Flow Matching Policy Optimization with Mirror Descent and Entropy Constraints","date":"2026-03-18","month_inferred_from_arxiv_id":null,"title_source":"syntology","repo":"lzqw/FLAME","path":"analysis/collect_exp37_results.py","file_url":"https://github.com/lzqw/FLAME/blob/HEAD/analysis/collect_exp37_results.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"4fbcb926264f78c1","mcp_get_code":{"code_sha256":"4fbcb926264f78c1"}},{"arxiv_id":"2506.05982","paper":"/paper/mca-bench-a-multimodal-benchmark-for","title":"MCA-Bench: A Multimodal Benchmark for Evaluating CAPTCHA Robustness Against VLM-based Attacks","date":"2025-06-06","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"noheadwuzonglin/mca-bench","path":"tojson/clickmathtojson.py","file_url":"https://github.com/noheadwuzonglin/mca-bench/blob/HEAD/tojson/clickmathtojson.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":"9ffd56c767ed71fd","mcp_get_code":{"code_sha256":"9ffd56c767ed71fd"}},{"arxiv_id":"2006.05553","paper":"/paper/neural-methods-for-point-wise-dependency","title":"Neural Methods for Point-wise Dependency Estimation","date":"2020-06-09","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"yaohungt/Pointwise_Dependency_Neural_Estimation","path":"RepreLearn_Deep/FastAutoAugment/imagenet.py","file_url":"https://github.com/yaohungt/Pointwise_Dependency_Neural_Estimation/blob/HEAD/RepreLearn_Deep/FastAutoAugment/imagenet.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"97bfaa2cce837d67","mcp_get_code":{"code_sha256":"97bfaa2cce837d67"}},{"arxiv_id":"2003.03780","paper":"/paper/dada-differentiable-automatic-data","title":"DADA: Differentiable Automatic Data Augmentation","date":"2020-03-08","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"VDIGPKU/DADA","path":"search_gumbel/imagenet.py","file_url":"https://github.com/VDIGPKU/DADA/blob/HEAD/search_gumbel/imagenet.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"97bfaa2cce837d67","mcp_get_code":{"code_sha256":"97bfaa2cce837d67"}},{"arxiv_id":"1905.00397","paper":"/paper/fast-autoaugment","title":"Fast AutoAugment","date":"2019-05-01","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"kakaobrain/fast-autoaugment","path":"FastAutoAugment/imagenet.py","file_url":"https://github.com/kakaobrain/fast-autoaugment/blob/HEAD/FastAutoAugment/imagenet.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"97bfaa2cce837d67","mcp_get_code":{"code_sha256":"97bfaa2cce837d67"}},{"arxiv_id":"Mao_Cross-Rejective_Open-Set_SAR_Image_Registration_CVPR_2025_paper","paper":null,"title":"arXiv:Mao_Cross-Rejective_Open-Set_SAR_Image_Registration_CVPR_2025_paper","date":null,"month_inferred_from_arxiv_id":null,"title_source":null,"repo":"XDyaoshi/CroR-OSIR-main","path":"CroR-OSIR-main-version-two/RandAugment/imagenet.py","file_url":"https://github.com/XDyaoshi/CroR-OSIR-main/blob/HEAD/CroR-OSIR-main-version-two/RandAugment/imagenet.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":"97bfaa2cce837d67","mcp_get_code":{"code_sha256":"97bfaa2cce837d67"}}]}