{"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/basedetector","entry":"BaseDetector","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":3,"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":4,"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":"2607.12523","paper":"/paper/arxiv-2607-12523","title":"OOD-RL-Bench: A Benchmark Framework for Out-of-Distribution Detection in Reinforcement Learning","date":null,"month_inferred_from_arxiv_id":"2026-07","title_source":"syntology","repo":"ood-rl-bench/ood-rl-bench","path":"ood_rl_bench/core/benchmark.py","file_url":"https://github.com/ood-rl-bench/ood-rl-bench/blob/HEAD/ood_rl_bench/core/benchmark.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":"9efbe03a7851253a","mcp_get_code":{"code_sha256":"9efbe03a7851253a"}},{"arxiv_id":"2603.12916","paper":"/paper/arxiv-2603-12916","title":"Surprised by Attention: Predictable Query Dynamics for Time Series Anomaly Detection","date":null,"month_inferred_from_arxiv_id":"2026-03","title_source":"syntology","repo":"iis-esslingen/AxonAD","path":"TSB_AD/models/AxonAD.py","file_url":"https://github.com/iis-esslingen/AxonAD/blob/HEAD/TSB_AD/models/AxonAD.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":"ff98834dc74659ef","mcp_get_code":{"code_sha256":"ff98834dc74659ef"}},{"arxiv_id":"2510.09259","paper":"/paper/arxiv-2510-09259","title":"Detecting Data Contamination from Reinforcement Learning Post-training for Large Language Models","date":null,"month_inferred_from_arxiv_id":"2025-10","title_source":"syntology","repo":"yongding-tao/RL-Data-Contamination","path":"detectors/self_critique.py","file_url":"https://github.com/yongding-tao/RL-Data-Contamination/blob/HEAD/detectors/self_critique.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"0b0bc9b6266d1e5f","mcp_get_code":{"code_sha256":"0b0bc9b6266d1e5f"}},{"arxiv_id":"2503.18286","paper":"/paper/co-spy-combining-semantic-and-pixel-features","title":"CO-SPY: Combining Semantic and Pixel Features to Detect Synthetic Images by AI","date":"2025-03-24","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"Megum1/Co-Spy","path":"detectors/progan/fusion.py","file_url":"https://github.com/Megum1/Co-Spy/blob/HEAD/detectors/progan/fusion.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"ea6444b2029dc4b3","mcp_get_code":{"code_sha256":"ea6444b2029dc4b3"}},{"arxiv_id":"2501.11971","paper":"/paper/smamba-sparse-mamba-for-event-based-object","title":"SMamba: Sparse Mamba for Event-based Object Detection","date":"2025-01-21","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"Zizzzzzzz/SMamba_AAAI2025","path":"models/detection/recurrent_backbone/SMamba.py","file_url":"https://github.com/Zizzzzzzz/SMamba_AAAI2025/blob/HEAD/models/detection/recurrent_backbone/SMamba.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":"deterministic","behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"e61ba2d147fae2d5","mcp_get_code":{"code_sha256":"e61ba2d147fae2d5"}},{"arxiv_id":"2403.16131","paper":"/paper/salience-detr-enhancing-detection-transformer-1","title":"Salience DETR: Enhancing Detection Transformer with Hierarchical Salience Filtering Refinement","date":"2024-03-24","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"xiuqhou/Salience-DETR","path":"models/detectors/salience_detr.py","file_url":"https://github.com/xiuqhou/Salience-DETR/blob/HEAD/models/detectors/salience_detr.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":"b6ec17c5de8153f5","mcp_get_code":{"code_sha256":"b6ec17c5de8153f5"}},{"arxiv_id":"2403.16131","paper":"/paper/salience-detr-enhancing-detection-transformer-1","title":"Salience DETR: Enhancing Detection Transformer with Hierarchical Salience Filtering Refinement","date":"2024-03-24","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"xunull/read-Salience-DETR","path":"models/detectors/salience_detr.py","file_url":"https://github.com/xunull/read-Salience-DETR/blob/HEAD/models/detectors/salience_detr.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":"b9d6e114bdfb48b5","mcp_get_code":{"code_sha256":"b9d6e114bdfb48b5"}},{"arxiv_id":"2306.14920","paper":"/paper/a-cosine-similarity-based-method-for-out-of","title":"A Cosine Similarity-based Method for Out-of-Distribution Detection","date":"2023-06-23","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"Fsoft-AIC/CTM_OOD","path":"core/detection/methods/post_hoc/ctm.py","file_url":"https://github.com/Fsoft-AIC/CTM_OOD/blob/HEAD/core/detection/methods/post_hoc/ctm.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"4f345573217a12a9","mcp_get_code":{"code_sha256":"4f345573217a12a9"}},{"arxiv_id":"2108.10312","paper":"/paper/exploring-simple-3d-multi-object-tracking-for","title":"Exploring Simple 3D Multi-Object Tracking for Autonomous Driving","date":"2021-08-23","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"qcraftai/simtrack","path":"det3d/models/detectors/single_stage.py","file_url":"https://github.com/qcraftai/simtrack/blob/HEAD/det3d/models/detectors/single_stage.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NOASSERTION","inline_ok":false,"code_sha256_prefix":"5cab2d1af877535f","mcp_get_code":{"code_sha256":"5cab2d1af877535f"}}]}