{"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/gather-results","entry":"gather_results","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":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":5,"n_samples_ran":1,"n_samples_fingerprinted":0,"n_places":5,"n_places_pointer_only":0,"by_status":{"ran_honours":0,"ran_violates":0,"ran_draft_wrong":0,"ran_fixture":0,"ran":1,"unverified":4},"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":"2609.02318","paper":"/paper/arxiv-2609-02318","title":"YesTrack: Referring Multi-Object Tracking via MLLM-based Yes/No Verification","date":null,"month_inferred_from_arxiv_id":"2026-09","title_source":"syntology","repo":"ggbondrighthere24/YesTrack","path":"refer_llm/llm_eval.py","file_url":"https://github.com/ggbondrighthere24/YesTrack/blob/HEAD/refer_llm/llm_eval.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"4cfa53ade4f9d2ef","mcp_get_code":{"code_sha256":"4cfa53ade4f9d2ef"}},{"arxiv_id":"2503.12559","paper":"/paper/adaretake-adaptive-redundancy-reduction-to","title":"AdaReTaKe: Adaptive Redundancy Reduction to Perceive Longer for Video-language Understanding","date":"2025-03-16","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"sczwangxiao/video-flexreduc","path":"retake/infer_eval.py","file_url":"https://github.com/sczwangxiao/video-flexreduc/blob/HEAD/retake/infer_eval.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"e1e87b90e35fb630","mcp_get_code":{"code_sha256":"e1e87b90e35fb630"}},{"arxiv_id":"2410.13032","paper":"/paper/hypothesis-testing-the-circuit-hypothesis-in","title":"Hypothesis Testing the Circuit Hypothesis in LLMs","date":"2024-10-16","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"blei-lab/circuitry","path":"paper_experiments/figures/generate_figures.py","file_url":"https://github.com/blei-lab/circuitry/blob/HEAD/paper_experiments/figures/generate_figures.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"07119487f732c8aa","mcp_get_code":{"code_sha256":"07119487f732c8aa"}},{"arxiv_id":"2404.07762","paper":"/paper/neuroncap-photorealistic-closed-loop-safety","title":"NeuroNCAP: Photorealistic Closed-loop Safety Testing for Autonomous Driving","date":"2024-04-11","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"atonderski/neuro-ncap","path":"scripts/aggregate_results.py","file_url":"https://github.com/atonderski/neuro-ncap/blob/HEAD/scripts/aggregate_results.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"ef6e2f3ee863e8b7","mcp_get_code":{"code_sha256":"ef6e2f3ee863e8b7"}},{"arxiv_id":"1803.09196","paper":"/paper/learning-type-aware-embeddings-for-fashion","title":"Learning Type-Aware Embeddings for Fashion Compatibility","date":"2018-03-25","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"owj0421/DeepFashion","path":"src/utils/distributed_utils.py","file_url":"https://github.com/owj0421/DeepFashion/blob/HEAD/src/utils/distributed_utils.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":"31d8ae5162014982","mcp_get_code":{"code_sha256":"31d8ae5162014982"}}]}