{"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/get-energy-score","entry":"get_energy_score","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":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":4,"n_samples_ran":1,"n_samples_fingerprinted":0,"n_places":5,"n_places_pointer_only":5,"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":"2507.09924","paper":null,"title":"arXiv:2507.09924","date":null,"month_inferred_from_arxiv_id":"2025-07","title_source":null,"repo":"LouisDo2108/MixLoRA-DSI","path":"t5_pretrainer/mixlora_varigrow.py","file_url":"https://github.com/LouisDo2108/MixLoRA-DSI/blob/HEAD/t5_pretrainer/mixlora_varigrow.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"cd6c304b3954e0d5","mcp_get_code":{"code_sha256":"cd6c304b3954e0d5"}},{"arxiv_id":"2411.14049","paper":"/paper/out-of-distribution-detection-with-1","title":"Out-Of-Distribution Detection with Diversification (Provably)","date":"2024-11-21","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"haiyunyao/diversemix","path":"eval_ood_detection.py","file_url":"https://github.com/haiyunyao/diversemix/blob/HEAD/eval_ood_detection.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"486627d2c362021e","mcp_get_code":{"code_sha256":"486627d2c362021e"}},{"arxiv_id":"2410.18472","paper":"/paper/what-if-the-input-is-expanded-in-ood","title":"What If the Input is Expanded in OOD Detection?","date":"2024-10-24","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"tmlr-group/CoVer","path":"DNNs/ash.py","file_url":"https://github.com/tmlr-group/CoVer/blob/HEAD/DNNs/ash.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"ae606c71d60fc894","mcp_get_code":{"code_sha256":"ae606c71d60fc894"}},{"arxiv_id":"2308.10239","paper":"/paper/from-global-to-local-multi-scale-out-of","title":"From Global to Local: Multi-scale Out-of-distribution Detection","date":"2023-08-20","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"jimzai/mode-ood","path":"util/score.py","file_url":"https://github.com/jimzai/mode-ood/blob/HEAD/util/score.py","status":"ran_draft_wrong","verification_level":1,"contract_check":"MISDECLARED","metamorphic_tier":"invariant","behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"209469a90d2f8a72","mcp_get_code":{"code_sha256":"209469a90d2f8a72"}},{"arxiv_id":"2204.06507","paper":"/paper/out-of-distribution-detection-with-deep","title":"Out-of-Distribution Detection with Deep Nearest Neighbors","date":"2022-04-13","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"deeplearning-wisc/knn-ood","path":"util/score.py","file_url":"https://github.com/deeplearning-wisc/knn-ood/blob/HEAD/util/score.py","status":"ran_draft_wrong","verification_level":1,"contract_check":"MISDECLARED","metamorphic_tier":"invariant","behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"209469a90d2f8a72","mcp_get_code":{"code_sha256":"209469a90d2f8a72"}}]}