{"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/unlearncollector","entry":"unlearncollector","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":7,"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":2,"n_samples_fingerprinted":0,"n_places":7,"n_places_pointer_only":2,"by_status":{"ran_honours":0,"ran_violates":0,"ran_draft_wrong":0,"ran_fixture":0,"ran":2,"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":"2605.08765","paper":"/paper/arxiv-2605-08765","title":"Unlearners Can Lie: Evaluating and Improving Honesty in LLM Unlearning","date":null,"month_inferred_from_arxiv_id":"2026-05","title_source":"syntology","repo":"OPTML-Group/ReVa","path":"src/eval/dataset/Base.py","file_url":"https://github.com/OPTML-Group/ReVa/blob/HEAD/src/eval/dataset/Base.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"a378b7ead7ef288e","mcp_get_code":{"code_sha256":"a378b7ead7ef288e"}},{"arxiv_id":"2605.06076","paper":"/paper/arxiv-2605-06076","title":"Navigating by Old Maps: The Pitfalls of Static Mechanistic Localization in LLM Post-Training","date":null,"month_inferred_from_arxiv_id":"2026-05","title_source":"syntology","repo":"Zodiark-ch/MechLocalization","path":"src/dataset/Base.py","file_url":"https://github.com/Zodiark-ch/MechLocalization/blob/HEAD/src/dataset/Base.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"365b264039b356f2","mcp_get_code":{"code_sha256":"365b264039b356f2"}},{"arxiv_id":"2506.01339","paper":"/paper/invariance-makes-llm-unlearning-resilient","title":"Invariance Makes LLM Unlearning Resilient Even to Unanticipated Downstream Fine-Tuning","date":"2025-06-02","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"OPTML-Group/Unlearn-ILU","path":"src/dataset/Base.py","file_url":"https://github.com/OPTML-Group/Unlearn-ILU/blob/HEAD/src/dataset/Base.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"21b851de3f5356c4","mcp_get_code":{"code_sha256":"21b851de3f5356c4"}},{"arxiv_id":"2410.17509","paper":"/paper/wagle-strategic-weight-attribution-for","title":"WAGLE: Strategic Weight Attribution for Effective and Modular Unlearning in Large Language Models","date":"2024-10-23","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"OPTML-Group/WAGLE","path":"src/dataset/Base.py","file_url":"https://github.com/OPTML-Group/WAGLE/blob/HEAD/src/dataset/Base.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"21b851de3f5356c4","mcp_get_code":{"code_sha256":"21b851de3f5356c4"}},{"arxiv_id":"2410.07163","paper":"/paper/simplicity-prevails-rethinking-negative","title":"Simplicity Prevails: Rethinking Negative Preference Optimization for LLM Unlearning","date":"2024-10-09","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"OPTML-Group/Unlearn-Simple","path":"TOFU/data_module.py","file_url":"https://github.com/OPTML-Group/Unlearn-Simple/blob/HEAD/TOFU/data_module.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"52f769b837c6e32a","mcp_get_code":{"code_sha256":"52f769b837c6e32a"}},{"arxiv_id":"2404.18239","paper":"/paper/soul-unlocking-the-power-of-second-order","title":"SOUL: Unlocking the Power of Second-Order Optimization for LLM Unlearning","date":"2024-04-28","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"optml-group/soul","path":"src/dataset/Base.py","file_url":"https://github.com/optml-group/soul/blob/HEAD/src/dataset/Base.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"21b851de3f5356c4","mcp_get_code":{"code_sha256":"21b851de3f5356c4"}},{"arxiv_id":"2025.findings-acl.949","paper":null,"title":"arXiv:2025.findings-acl.949","date":null,"month_inferred_from_arxiv_id":null,"title_source":null,"repo":"renjie3/GRUN","path":"baseline/data_module.py","file_url":"https://github.com/renjie3/GRUN/blob/HEAD/baseline/data_module.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"52f769b837c6e32a","mcp_get_code":{"code_sha256":"52f769b837c6e32a"}}]}