{"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/kl-loc-loss","entry":"kl_loc_loss","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":28,"n_papers_ran":10,"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":3,"n_samples_ran":1,"n_samples_fingerprinted":0,"n_places":28,"n_places_pointer_only":12,"by_status":{"ran_honours":0,"ran_violates":0,"ran_draft_wrong":0,"ran_fixture":0,"ran":1,"unverified":2},"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":"2607.01978","paper":"/paper/arxiv-2607-01978","title":"Multimodal Knowledge Edit-Scoped Generalization for Online Recursive MLLM Editing","date":null,"month_inferred_from_arxiv_id":"2026-07","title_source":"syntology","repo":"lab-klc/ScopeEdit","path":"easyeditor/trainer/losses.py","file_url":"https://github.com/lab-klc/ScopeEdit/blob/HEAD/easyeditor/trainer/losses.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"bcc592aa5c1e2bb3","mcp_get_code":{"code_sha256":"bcc592aa5c1e2bb3"}},{"arxiv_id":"2605.26670","paper":"/paper/arxiv-2605-26670","title":"The Labyrinth and the Thread: Rethinking Regularizations in Sequential Knowledge Editing for Large Language Models","date":null,"month_inferred_from_arxiv_id":"2026-05","title_source":"syntology","repo":"Wangzzzzzzzz/OTE-SE-Alignment","path":"baselines/mend/losses.py","file_url":"https://github.com/Wangzzzzzzzz/OTE-SE-Alignment/blob/HEAD/baselines/mend/losses.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"8b02eb3a3733d653","mcp_get_code":{"code_sha256":"8b02eb3a3733d653"}},{"arxiv_id":"2601.07873","paper":"/paper/arxiv-2601-07873","title":"Multiplicative Orthogonal Sequential Editing for Language Models","date":null,"month_inferred_from_arxiv_id":"2026-01","title_source":"syntology","repo":"famoustourist/MOSE","path":"easyeditor/trainer/losses.py","file_url":"https://github.com/famoustourist/MOSE/blob/HEAD/easyeditor/trainer/losses.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"bcc592aa5c1e2bb3","mcp_get_code":{"code_sha256":"bcc592aa5c1e2bb3"}},{"arxiv_id":"2502.19870","paper":"/paper/mmke-bench-a-multimodal-editing-benchmark-for","title":"MMKE-Bench: A Multimodal Editing Benchmark for Diverse Visual Knowledge","date":"2025-02-27","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"MMKE-Bench-ICLR/MMKE-Bench","path":"easyeditor/trainer/losses.py","file_url":"https://github.com/MMKE-Bench-ICLR/MMKE-Bench/blob/HEAD/easyeditor/trainer/losses.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"bcc592aa5c1e2bb3","mcp_get_code":{"code_sha256":"bcc592aa5c1e2bb3"}},{"arxiv_id":"2502.11177","paper":"/paper/the-mirage-of-model-editing-revisiting","title":"The Mirage of Model Editing: Revisiting Evaluation in the Wild","date":"2025-02-16","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"wanliyoung/revisit-editing-evaluation","path":"easyeditor/trainer/losses.py","file_url":"https://github.com/wanliyoung/revisit-editing-evaluation/blob/HEAD/easyeditor/trainer/losses.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":"bcc592aa5c1e2bb3","mcp_get_code":{"code_sha256":"bcc592aa5c1e2bb3"}},{"arxiv_id":"2502.03748","paper":null,"title":"arXiv:2502.03748","date":null,"month_inferred_from_arxiv_id":"2025-02","title_source":null,"repo":"xpq-tech/BLUE","path":"baselines/mend/losses.py","file_url":"https://github.com/xpq-tech/BLUE/blob/HEAD/baselines/mend/losses.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"8b02eb3a3733d653","mcp_get_code":{"code_sha256":"8b02eb3a3733d653"}},{"arxiv_id":"2410.18785","paper":"/paper/should-we-really-edit-language-models-on-the","title":"Should We Really Edit Language Models? On the Evaluation of Edited Language Models","date":"2024-10-24","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"zjunlp/EasyEdit","path":"easyeditor/trainer/losses.py","file_url":"https://github.com/zjunlp/EasyEdit/blob/HEAD/easyeditor/trainer/losses.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"bcc592aa5c1e2bb3","mcp_get_code":{"code_sha256":"bcc592aa5c1e2bb3"}},{"arxiv_id":"2410.16251","paper":"/paper/can-knowledge-editing-really-correct","title":"Can Knowledge Editing Really Correct Hallucinations?","date":"2024-10-21","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"llm-editing/HalluEditBench","path":"code/easyeditor/trainer/losses.py","file_url":"https://github.com/llm-editing/HalluEditBench/blob/HEAD/code/easyeditor/trainer/losses.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"bcc592aa5c1e2bb3","mcp_get_code":{"code_sha256":"bcc592aa5c1e2bb3"}},{"arxiv_id":"2410.09508","paper":"/paper/collabedit-towards-non-destructive","title":"CollabEdit: Towards Non-destructive Collaborative Knowledge Editing","date":"2024-10-12","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"LINs-lab/CollabEdit","path":"baselines/mend/losses.py","file_url":"https://github.com/LINs-lab/CollabEdit/blob/HEAD/baselines/mend/losses.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"8b02eb3a3733d653","mcp_get_code":{"code_sha256":"8b02eb3a3733d653"}},{"arxiv_id":"2410.04045","paper":"/paper/neuron-level-sequential-editing-for-large","title":"Neuron-Level Sequential Editing for Large Language Models","date":"2024-10-05","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"jianghoucheng/nse","path":"baselines/mend/losses.py","file_url":"https://github.com/jianghoucheng/nse/blob/HEAD/baselines/mend/losses.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"8b02eb3a3733d653","mcp_get_code":{"code_sha256":"8b02eb3a3733d653"}},{"arxiv_id":"2407.20224","paper":"/paper/can-editing-llms-inject-harm","title":"Can Editing LLMs Inject Harm?","date":"2024-07-29","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"llm-editing/editing-attack","path":"code/easyeditor/trainer/losses.py","file_url":"https://github.com/llm-editing/editing-attack/blob/HEAD/code/easyeditor/trainer/losses.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"bcc592aa5c1e2bb3","mcp_get_code":{"code_sha256":"bcc592aa5c1e2bb3"}},{"arxiv_id":"2407.06483","paper":"/paper/composable-interventions-for-language-models","title":"Composable Interventions for Language Models","date":"2024-07-09","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"hartvigsen-group/composable-interventions","path":"easyeditor/trainer/losses.py","file_url":"https://github.com/hartvigsen-group/composable-interventions/blob/HEAD/easyeditor/trainer/losses.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"bcc592aa5c1e2bb3","mcp_get_code":{"code_sha256":"bcc592aa5c1e2bb3"}},{"arxiv_id":"2406.11614","paper":"/paper/intrinsic-evaluation-of-unlearning-using","title":"Intrinsic Evaluation of Unlearning Using Parametric Knowledge Traces","date":"2024-06-17","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"yihuaihong/conceptvectors","path":"memit/baselines/mend/losses.py","file_url":"https://github.com/yihuaihong/conceptvectors/blob/HEAD/memit/baselines/mend/losses.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"CC-BY-4.0","inline_ok":false,"code_sha256_prefix":"8b02eb3a3733d653","mcp_get_code":{"code_sha256":"8b02eb3a3733d653"}},{"arxiv_id":"2406.11194","paper":"/paper/in-context-editing-learning-knowledge-from","title":"In-Context Editing: Learning Knowledge from Self-Induced Distributions","date":"2024-06-17","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"bigai-ai/ICE","path":"easyeditor/trainer/losses.py","file_url":"https://github.com/bigai-ai/ICE/blob/HEAD/easyeditor/trainer/losses.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"bcc592aa5c1e2bb3","mcp_get_code":{"code_sha256":"bcc592aa5c1e2bb3"}},{"arxiv_id":"2405.16821","paper":"/paper/perturbation-restrained-sequential-model","title":"Perturbation-Restrained Sequential Model Editing","date":"2024-05-27","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"mjy1111/PRUNE","path":"easyeditor/trainer/losses.py","file_url":"https://github.com/mjy1111/PRUNE/blob/HEAD/easyeditor/trainer/losses.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"bcc592aa5c1e2bb3","mcp_get_code":{"code_sha256":"bcc592aa5c1e2bb3"}},{"arxiv_id":"2404.15004","paper":"/paper/taxi-evaluating-categorical-knowledge-editing","title":"TAXI: Evaluating Categorical Knowledge Editing for Language Models","date":"2024-04-23","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"derekpowell/taxi","path":"easyeditor/trainer/losses.py","file_url":"https://github.com/derekpowell/taxi/blob/HEAD/easyeditor/trainer/losses.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"bcc592aa5c1e2bb3","mcp_get_code":{"code_sha256":"bcc592aa5c1e2bb3"}},{"arxiv_id":"2403.14364","paper":"/paper/wikifactdiff-a-large-realistic-and-temporally","title":"WikiFactDiff: A Large, Realistic, and Temporally Adaptable Dataset for Atomic Factual Knowledge Update in Causal Language Models","date":"2024-03-21","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"orange-opensource/wikifactdiff","path":"evaluate/baselines/mend/losses.py","file_url":"https://github.com/orange-opensource/wikifactdiff/blob/HEAD/evaluate/baselines/mend/losses.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"8b02eb3a3733d653","mcp_get_code":{"code_sha256":"8b02eb3a3733d653"}},{"arxiv_id":"2403.07350","paper":"/paper/kebench-a-benchmark-on-knowledge-editing-for","title":"VLKEB: A Large Vision-Language Model Knowledge Editing Benchmark","date":"2024-03-12","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"VLKEB/VLKEB","path":"easyeditor/trainer/losses.py","file_url":"https://github.com/VLKEB/VLKEB/blob/HEAD/easyeditor/trainer/losses.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"bcc592aa5c1e2bb3","mcp_get_code":{"code_sha256":"bcc592aa5c1e2bb3"}},{"arxiv_id":"2403.07175","paper":"/paper/rebuilding-rome-resolving-model-collapse","title":"Rebuilding ROME : Resolving Model Collapse during Sequential Model Editing","date":"2024-03-11","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"scalable-model-editing/rebuilding-rome","path":"baselines/mend/losses.py","file_url":"https://github.com/scalable-model-editing/rebuilding-rome/blob/HEAD/baselines/mend/losses.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"8b02eb3a3733d653","mcp_get_code":{"code_sha256":"8b02eb3a3733d653"}},{"arxiv_id":"2402.11905","paper":"/paper/learning-to-edit-aligning-llms-with-knowledge","title":"Learning to Edit: Aligning LLMs with Knowledge Editing","date":"2024-02-19","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"yjiangcm/lte","path":"EasyEdit/easyeditor/trainer/losses.py","file_url":"https://github.com/yjiangcm/lte/blob/HEAD/EasyEdit/easyeditor/trainer/losses.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":"bcc592aa5c1e2bb3","mcp_get_code":{"code_sha256":"bcc592aa5c1e2bb3"}},{"arxiv_id":"2401.17623","paper":"/paper/neighboring-perturbations-of-knowledge","title":"Neighboring Perturbations of Knowledge Editing on Large Language Models","date":"2024-01-31","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"mjy1111/PEAK","path":"easyeditor/trainer/losses.py","file_url":"https://github.com/mjy1111/PEAK/blob/HEAD/easyeditor/trainer/losses.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"bcc592aa5c1e2bb3","mcp_get_code":{"code_sha256":"bcc592aa5c1e2bb3"}},{"arxiv_id":"2401.07453","paper":"/paper/model-editing-at-scale-leads-to-gradual-and","title":"Model Editing at Scale leads to Gradual and Catastrophic Forgetting","date":"2024-01-15","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"scalable-model-editing/gradual-catastrophic-forgetting","path":"baselines/mend/losses.py","file_url":"https://github.com/scalable-model-editing/gradual-catastrophic-forgetting/blob/HEAD/baselines/mend/losses.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"8b02eb3a3733d653","mcp_get_code":{"code_sha256":"8b02eb3a3733d653"}},{"arxiv_id":"2401.04700","paper":"/paper/model-editing-can-hurt-general-abilities-of","title":"Model Editing Harms General Abilities of Large Language Models: Regularization to the Rescue","date":"2024-01-09","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"jasonforjoy/model-editing-hurt","path":"easyeditor/trainer/losses.py","file_url":"https://github.com/jasonforjoy/model-editing-hurt/blob/HEAD/easyeditor/trainer/losses.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"bcc592aa5c1e2bb3","mcp_get_code":{"code_sha256":"bcc592aa5c1e2bb3"}},{"arxiv_id":"2311.09053","paper":"/paper/assessing-knowledge-editing-in-language","title":"Assessing Knowledge Editing in Language Models via Relation Perspective","date":"2023-11-15","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"weiyifan1023/knowledge-edit-based-on-relation-perspective","path":"baselines/mend/losses.py","file_url":"https://github.com/weiyifan1023/knowledge-edit-based-on-relation-perspective/blob/HEAD/baselines/mend/losses.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"8b02eb3a3733d653","mcp_get_code":{"code_sha256":"8b02eb3a3733d653"}},{"arxiv_id":"2310.10322","paper":"/paper/untying-the-reversal-curse-via-bidirectional","title":"Untying the Reversal Curse via Bidirectional Language Model Editing","date":"2023-10-16","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"mjy1111/bake","path":"easyeditor/trainer/losses.py","file_url":"https://github.com/mjy1111/bake/blob/HEAD/easyeditor/trainer/losses.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"bcc592aa5c1e2bb3","mcp_get_code":{"code_sha256":"bcc592aa5c1e2bb3"}},{"arxiv_id":"2210.07229","paper":"/paper/mass-editing-memory-in-a-transformer","title":"Mass-Editing Memory in a Transformer","date":"2022-10-13","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"kmeng01/memit","path":"baselines/mend/losses.py","file_url":"https://github.com/kmeng01/memit/blob/HEAD/baselines/mend/losses.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"8b02eb3a3733d653","mcp_get_code":{"code_sha256":"8b02eb3a3733d653"}},{"arxiv_id":"Zeng_Visual-Oriented_Fine-Grained_Knowledge_Editing_for_MultiModal_Large_Language_Models_ICCV_2025_paper","paper":null,"title":"arXiv:Zeng_Visual-Oriented_Fine-Grained_Knowledge_Editing_for_MultiModal_Large_Language_Models_ICCV_2025_paper","date":null,"month_inferred_from_arxiv_id":null,"title_source":null,"repo":"zeng-zhen/FGVEdit","path":"easyeditor/trainer/losses.py","file_url":"https://github.com/zeng-zhen/FGVEdit/blob/HEAD/easyeditor/trainer/losses.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"bcc592aa5c1e2bb3","mcp_get_code":{"code_sha256":"bcc592aa5c1e2bb3"}},{"arxiv_id":"2024.acl-long.732","paper":null,"title":"arXiv:2024.acl-long.732","date":null,"month_inferred_from_arxiv_id":null,"title_source":null,"repo":"wchrepo/mulfe","path":"evaluation/baselines/mend/losses.py","file_url":"https://github.com/wchrepo/mulfe/blob/HEAD/evaluation/baselines/mend/losses.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":"b5ffa288849b3969","mcp_get_code":{"code_sha256":"b5ffa288849b3969"}}]}