{"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/make-encoder","entry":"make_encoder","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":15,"n_papers_ran":5,"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":12,"n_samples_ran":5,"n_samples_fingerprinted":0,"n_places":15,"n_places_pointer_only":5,"by_status":{"ran_honours":0,"ran_violates":0,"ran_draft_wrong":4,"ran_fixture":1,"ran":0,"unverified":7},"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":"2608.20400","paper":"/paper/arxiv-2608-20400","title":"When Retrieval Fails Before It Begins: Structurally Indirect Prerequisite Eviction as a Retention Failure in Agentic Memory","date":null,"month_inferred_from_arxiv_id":"2026-08","title_source":"syntology","repo":"smkgenesis/dsgc","path":"src/benchmarking/policy.py","file_url":"https://github.com/smkgenesis/dsgc/blob/HEAD/src/benchmarking/policy.py","status":"ran_fixture","verification_level":1,"contract_check":"DEP_MISSING","metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"547b9712bd0ef152","mcp_get_code":{"code_sha256":"547b9712bd0ef152"}},{"arxiv_id":"2505.16734","paper":"/paper/maximum-total-correlation-reinforcement","title":"Maximum Total Correlation Reinforcement Learning","date":"2025-05-22","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"bangyou01/mtc","path":"tcsac.py","file_url":"https://github.com/bangyou01/mtc/blob/HEAD/tcsac.py","status":"ran_draft_wrong","verification_level":1,"contract_check":"MISDECLARED","metamorphic_tier":"deterministic","behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"194b6301d0fceef1","mcp_get_code":{"code_sha256":"194b6301d0fceef1"}},{"arxiv_id":"2404.05163","paper":"/paper/semantic-flow-learning-semantic-field-of","title":"Semantic Flow: Learning Semantic Field of Dynamic Scenes from Monocular Videos","date":"2024-04-08","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"tianfr/Semantic-Flow","path":"src/model/model_util.py","file_url":"https://github.com/tianfr/Semantic-Flow/blob/HEAD/src/model/model_util.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NOASSERTION","inline_ok":false,"code_sha256_prefix":"0b8b108e334214af","mcp_get_code":{"code_sha256":"0b8b108e334214af"}},{"arxiv_id":"2309.13039","paper":"/paper/nerrf-3d-reconstruction-and-view-synthesis","title":"NeRRF: 3D Reconstruction and View Synthesis for Transparent and Specular Objects with Neural Refractive-Reflective Fields","date":"2023-09-22","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"dawning77/nerrf","path":"src/model/model_util.py","file_url":"https://github.com/dawning77/nerrf/blob/HEAD/src/model/model_util.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"09578629f7267e4b","mcp_get_code":{"code_sha256":"09578629f7267e4b"}},{"arxiv_id":"2303.12786","paper":"/paper/featurenerf-learning-generalizable-nerfs-by","title":"FeatureNeRF: Learning Generalizable NeRFs by Distilling Foundation Models","date":"2023-03-22","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"jianglongye/featurenerf","path":"src/model/model_util.py","file_url":"https://github.com/jianglongye/featurenerf/blob/HEAD/src/model/model_util.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"09578629f7267e4b","mcp_get_code":{"code_sha256":"09578629f7267e4b"}},{"arxiv_id":"2206.05266","paper":"/paper/does-self-supervised-learning-really-improve","title":"Does Self-supervised Learning Really Improve Reinforcement Learning from Pixels?","date":"2022-06-10","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"LostXine/elo-sac","path":"encoder.py","file_url":"https://github.com/LostXine/elo-sac/blob/HEAD/encoder.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"ced159fb4f2d853b","mcp_get_code":{"code_sha256":"ced159fb4f2d853b"}},{"arxiv_id":"2205.00943","paper":"/paper/cclf-a-contrastive-curiosity-driven-learning","title":"CCLF: A Contrastive-Curiosity-Driven Learning Framework for Sample-Efficient Reinforcement Learning","date":"2022-05-02","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"csun001/CCLF","path":"CCLF_sac.py","file_url":"https://github.com/csun001/CCLF/blob/HEAD/CCLF_sac.py","status":"ran_draft_wrong","verification_level":1,"contract_check":"MISDECLARED","metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"59924c8a15d17e2f","mcp_get_code":{"code_sha256":"59924c8a15d17e2f"}},{"arxiv_id":"2107.02156","paper":"/paper/do-different-tracking-tasks-require-different","title":"Do Different Tracking Tasks Require Different Appearance Models?","date":"2021-07-05","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"Zhongdao/UniTrack","path":"model/model.py","file_url":"https://github.com/Zhongdao/UniTrack/blob/HEAD/model/model.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"d3b2fda956486d2c","mcp_get_code":{"code_sha256":"d3b2fda956486d2c"}},{"arxiv_id":"2010.09163","paper":"/paper/d2rl-deep-dense-architectures-in-1","title":"D2RL: Deep Dense Architectures in Reinforcement Learning","date":"2020-10-19","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"pairlab/d2rl","path":"curl/encoder.py","file_url":"https://github.com/pairlab/d2rl/blob/HEAD/curl/encoder.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"cd7d4d2ebf4b04c8","mcp_get_code":{"code_sha256":"cd7d4d2ebf4b04c8"}},{"arxiv_id":"2007.04309","paper":"/paper/self-supervised-policy-adaptation-during","title":"Self-Supervised Policy Adaptation during Deployment","date":"2020-07-08","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"nicklashansen/policy-adaptation-during-deployment","path":"src/agent/agent.py","file_url":"https://github.com/nicklashansen/policy-adaptation-during-deployment/blob/HEAD/src/agent/agent.py","status":"ran_draft_wrong","verification_level":1,"contract_check":"MISDECLARED","metamorphic_tier":"deterministic","behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"6dcb9b4b8ec4aabd","mcp_get_code":{"code_sha256":"6dcb9b4b8ec4aabd"}},{"arxiv_id":"2004.14990","paper":"/paper/reinforcement-learning-with-augmented-data","title":"Reinforcement Learning with Augmented Data","date":"2020-04-30","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"MishaLaskin/rad","path":"curl_sac.py","file_url":"https://github.com/MishaLaskin/rad/blob/HEAD/curl_sac.py","status":"ran_draft_wrong","verification_level":1,"contract_check":"MISDECLARED","metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"3ff1a7cb98f67025","mcp_get_code":{"code_sha256":"3ff1a7cb98f67025"}},{"arxiv_id":"2004.04136","paper":"/paper/curl-contrastive-unsupervised-representations","title":"CURL: Contrastive Unsupervised Representations for Reinforcement Learning","date":"2020-04-08","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"MishaLaskin/curl","path":"encoder.py","file_url":"https://github.com/MishaLaskin/curl/blob/HEAD/encoder.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"cd7d4d2ebf4b04c8","mcp_get_code":{"code_sha256":"cd7d4d2ebf4b04c8"}},{"arxiv_id":"1910.01741","paper":"/paper/improving-sample-efficiency-in-model-free-1","title":"Improving Sample Efficiency in Model-Free Reinforcement Learning from Images","date":"2019-10-02","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"denisyarats/pytorch_sac_ae","path":"encoder.py","file_url":"https://github.com/denisyarats/pytorch_sac_ae/blob/HEAD/encoder.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"b41b083f7956cdf2","mcp_get_code":{"code_sha256":"b41b083f7956cdf2"}},{"arxiv_id":"1903.10663","paper":"/paper/combination-of-multiple-global-descriptors","title":"Combination of Multiple Global Descriptors for Image Retrieval","date":"2019-03-26","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"Samjoel3101/Self-Supervised-Learning-fastai2","path":"ssl_fastai2/utils.py","file_url":"https://github.com/Samjoel3101/Self-Supervised-Learning-fastai2/blob/HEAD/ssl_fastai2/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":"aa08b32d313cbc98","mcp_get_code":{"code_sha256":"aa08b32d313cbc98"}},{"arxiv_id":"aaai_28229","paper":null,"title":"arXiv:aaai_28229","date":null,"month_inferred_from_arxiv_id":null,"title_source":null,"repo":"eezkni/ColNeRF","path":"src/model/model_util.py","file_url":"https://github.com/eezkni/ColNeRF/blob/HEAD/src/model/model_util.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"BSD-2-Clause","inline_ok":true,"code_sha256_prefix":"09578629f7267e4b","mcp_get_code":{"code_sha256":"09578629f7267e4b"}}]}