{"id":"https://openalex.org/W7117540895","doi":"https://doi.org/10.1145/3733799.3762973","title":"LLM Unlearning on Noisy Forget Sets: A Study of Incomplete, Rewritten, and Watermarked Data","display_name":"LLM Unlearning on Noisy Forget Sets: A Study of Incomplete, Rewritten, and Watermarked Data","publication_year":2025,"publication_date":"2025-10-13","ids":{"openalex":"https://openalex.org/W7117540895","doi":"https://doi.org/10.1145/3733799.3762973"},"language":null,"primary_location":{"id":"doi:10.1145/3733799.3762973","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3733799.3762973","pdf_url":null,"source":null,"license":"cc-by-nd","license_id":"https://openalex.org/licenses/cc-by-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 18th ACM Workshop on Artificial Intelligence and Security","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1145/3733799.3762973","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Changsheng Wang","orcid":"https://orcid.org/0009-0007-0957-638X"},"institutions":[{"id":"https://openalex.org/I87216513","display_name":"Michigan State University","ror":"https://ror.org/05hs6h993","country_code":"US","type":"education","lineage":["https://openalex.org/I87216513"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Changsheng Wang","raw_affiliation_strings":["Michigan State University, East Lansing, MI, USA"],"raw_orcid":"https://orcid.org/0009-0007-0957-638X","affiliations":[{"raw_affiliation_string":"Michigan State University, East Lansing, MI, USA","institution_ids":["https://openalex.org/I87216513"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5121550814","display_name":"Yihua Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I87216513","display_name":"Michigan State University","ror":"https://ror.org/05hs6h993","country_code":"US","type":"education","lineage":["https://openalex.org/I87216513"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yihua Zhang","raw_affiliation_strings":["Michigan State University, East Lansing, MI, USA"],"raw_orcid":"https://orcid.org/0000-0002-5147-9838","affiliations":[{"raw_affiliation_string":"Michigan State University, East Lansing, MI, USA","institution_ids":["https://openalex.org/I87216513"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103053820","display_name":"Dennis Wei","orcid":"https://orcid.org/0000-0002-6510-1537"},"institutions":[{"id":"https://openalex.org/I1341412227","display_name":"IBM (United States)","ror":"https://ror.org/05hh8d621","country_code":"US","type":"company","lineage":["https://openalex.org/I1341412227"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Dennis Wei","raw_affiliation_strings":["IBM Research, San jose, USA"],"raw_orcid":"https://orcid.org/0000-0002-6510-1537","affiliations":[{"raw_affiliation_string":"IBM Research, San jose, USA","institution_ids":["https://openalex.org/I1341412227"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5121541095","display_name":"Jinghan Jia","orcid":null},"institutions":[{"id":"https://openalex.org/I87216513","display_name":"Michigan State University","ror":"https://ror.org/05hs6h993","country_code":"US","type":"education","lineage":["https://openalex.org/I87216513"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jinghan Jia","raw_affiliation_strings":["Michigan State University, East Lansing, MI, USA"],"raw_orcid":"https://orcid.org/0009-0001-7753-2326","affiliations":[{"raw_affiliation_string":"Michigan State University, East Lansing, MI, USA","institution_ids":["https://openalex.org/I87216513"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5121554661","display_name":"Pin-Yu Chen","orcid":null},"institutions":[{"id":"https://openalex.org/I1341412227","display_name":"IBM (United States)","ror":"https://ror.org/05hh8d621","country_code":"US","type":"company","lineage":["https://openalex.org/I1341412227"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Pin-Yu Chen","raw_affiliation_strings":["IBM Research, San Jose, USA"],"raw_orcid":"https://orcid.org/0000-0003-1039-8369","affiliations":[{"raw_affiliation_string":"IBM Research, San Jose, USA","institution_ids":["https://openalex.org/I1341412227"]}]},{"author_position":"last","author":{"id":null,"display_name":"Sijia Liu","orcid":"https://orcid.org/0000-0003-2817-6991"},"institutions":[{"id":"https://openalex.org/I87216513","display_name":"Michigan State University","ror":"https://ror.org/05hs6h993","country_code":"US","type":"education","lineage":["https://openalex.org/I87216513"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sijia Liu","raw_affiliation_strings":["Michigan State University, East Lansing, MI, USA"],"raw_orcid":"https://orcid.org/0000-0003-2817-6991","affiliations":[{"raw_affiliation_string":"Michigan State University, East Lansing, MI, USA","institution_ids":["https://openalex.org/I87216513"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.673,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.88817022,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"136","last_page":"145"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.22349999845027924,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.22349999845027924,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.10920000076293945,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.04270000010728836,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/forgetting","display_name":"Forgetting","score":0.5694000124931335},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5619000196456909},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.4607999920845032},{"id":"https://openalex.org/keywords/memorization","display_name":"Memorization","score":0.44679999351501465},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.42570000886917114},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.4018999934196472},{"id":"https://openalex.org/keywords/benchmarking","display_name":"Benchmarking","score":0.3370000123977661},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.3174999952316284}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6815000176429749},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5746999979019165},{"id":"https://openalex.org/C7149132","wikidata":"https://www.wikidata.org/wiki/Q1377840","display_name":"Forgetting","level":2,"score":0.5694000124931335},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5619000196456909},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.48489999771118164},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.4607999920845032},{"id":"https://openalex.org/C30038468","wikidata":"https://www.wikidata.org/wiki/Q4354775","display_name":"Memorization","level":2,"score":0.44679999351501465},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.42570000886917114},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.4018999934196472},{"id":"https://openalex.org/C86251818","wikidata":"https://www.wikidata.org/wiki/Q816754","display_name":"Benchmarking","level":2,"score":0.3370000123977661},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.3174999952316284},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.30410000681877136},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.28189998865127563},{"id":"https://openalex.org/C2164484","wikidata":"https://www.wikidata.org/wiki/Q5170150","display_name":"Core (optical fiber)","level":2,"score":0.27959999442100525},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.2784000039100647},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.2766000032424927},{"id":"https://openalex.org/C2777179996","wikidata":"https://www.wikidata.org/wiki/Q911222","display_name":"Mistake","level":2,"score":0.27300000190734863},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.2702000141143799},{"id":"https://openalex.org/C188147891","wikidata":"https://www.wikidata.org/wiki/Q147638","display_name":"Cognitive science","level":1,"score":0.2669999897480011},{"id":"https://openalex.org/C90312973","wikidata":"https://www.wikidata.org/wiki/Q7449052","display_name":"Semantic data model","level":2,"score":0.25679999589920044},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.25}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3733799.3762973","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3733799.3762973","pdf_url":null,"source":null,"license":"cc-by-nd","license_id":"https://openalex.org/licenses/cc-by-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 18th ACM Workshop on Artificial Intelligence and Security","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3733799.3762973","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3733799.3762973","pdf_url":null,"source":null,"license":"cc-by-nd","license_id":"https://openalex.org/licenses/cc-by-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 18th ACM Workshop on Artificial Intelligence and Security","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":8,"referenced_works":["https://openalex.org/W2971296908","https://openalex.org/W3117572899","https://openalex.org/W4385570172","https://openalex.org/W4385572399","https://openalex.org/W4389524162","https://openalex.org/W4390790246","https://openalex.org/W4393147304","https://openalex.org/W4403680773"],"related_works":[],"abstract_inverted_index":{"Large":[0],"language":[1],"models":[2],"(LLMs)":[3],"exhibit":[4],"remarkable":[5],"generative":[6],"capabilities":[7],"but":[8],"raise":[9],"ethical":[10],"and":[11,20,103],"security":[12],"concerns":[13],"by":[14,158],"memorizing":[15],"sensitive":[16],"data,":[17,88],"reinforcing":[18],"biases,":[19],"producing":[21],"harmful":[22],"content.":[23],"These":[24],"risks":[25],"have":[26],"spurred":[27],"interest":[28],"in":[29,147],"LLM":[30,99],"unlearning,":[31],"the":[32,71,78],"task":[33],"of":[34,73,81],"removing":[35],"knowledge":[36],"associated":[37],"with":[38],"undesirable":[39],"data":[40,54,59],"from":[41],"pre-trained":[42],"models.":[43],"However,":[44],"most":[45],"existing":[46],"methods":[47],"assume":[48],"access":[49],"to":[50,90,117],"clean,":[51],"well-defined":[52],"forget":[53,58,87,93,108],"samples,":[55],"whereas":[56],"real-world":[57],"could":[60],"often":[61],"be":[62],"low-quality,":[63],"synthetically":[64],"rewritten,":[65],"or":[66,85],"watermarked,":[67],"casting":[68],"doubt":[69],"on":[70,105],"reliability":[72],"unlearning.":[74],"This":[75,150],"work":[76],"presents":[77],"first":[79],"study":[80],"unlearning":[82,100,113,153],"under":[83],"perturbed":[84],"low-fidelity":[86],"referred":[89],"as":[91],"noisy":[92,107],"sets.":[94],"By":[95],"systematically":[96],"benchmarking":[97],"state-of-the-art":[98],"methods,":[101],"RMU":[102],"NPO,":[104],"such":[106],"sets,":[109],"we":[110,130],"find":[111],"that":[112,120,138,152],"remains":[114],"surprisingly":[115],"robust":[116],"perturbations,":[118],"provided":[119],"core":[121],"semantic":[122,136,160],"signals":[123],"are":[124,155],"preserved.":[125],"To":[126],"explain":[127],"this":[128],"robustness,":[129],"propose":[131],"a":[132],"saliency-based":[133],"interpretation:":[134],"key":[135],"components":[137],"drive":[139],"forgetting":[140],"remain":[141],"consistently":[142],"influential":[143],"despite":[144],"substantial":[145],"variation":[146],"surface":[148],"form.":[149],"suggests":[151],"algorithms":[154],"primarily":[156],"guided":[157],"deep":[159],"cues":[161],"rather":[162],"than":[163],"shallow":[164],"lexical":[165],"patterns.":[166]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-12-30T00:00:00"}
