{"id":"https://openalex.org/W7163059729","doi":"https://doi.org/10.48550/arxiv.2605.30514","title":"MAAT: Multi-phase Adapter-Aware Targeted Unlearning","display_name":"MAAT: Multi-phase Adapter-Aware Targeted Unlearning","publication_year":2026,"publication_date":"2026-05-28","ids":{"openalex":"https://openalex.org/W7163059729","doi":"https://doi.org/10.48550/arxiv.2605.30514"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.30514","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.30514","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2605.30514","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5137591344","display_name":"Suryash Yagnik","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yagnik, Suryash","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047733952","display_name":"Shubham Gaur","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gaur, Shubham","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5123962032","display_name":"Saksham Thakur","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Thakur, Saksham","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137514238","display_name":"Vinija Jain","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jain, Vinija","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137596335","display_name":"Aman Chadha","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chadha, Aman","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5137523749","display_name":"Amitava Das","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Das, Amitava","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.7734000086784363,"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":0.7734000086784363,"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/T10181","display_name":"Natural Language Processing Techniques","score":0.03720000013709068,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.02199999988079071,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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":0.7325000166893005},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.4767000079154968},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.4456000030040741},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.4361000061035156},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.3490000069141388},{"id":"https://openalex.org/keywords/pareto-principle","display_name":"Pareto principle","score":0.34619998931884766}],"concepts":[{"id":"https://openalex.org/C7149132","wikidata":"https://www.wikidata.org/wiki/Q1377840","display_name":"Forgetting","level":2,"score":0.7325000166893005},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.550000011920929},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5271000266075134},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.4767000079154968},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.4456000030040741},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.4361000061035156},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3772999942302704},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.3490000069141388},{"id":"https://openalex.org/C137635306","wikidata":"https://www.wikidata.org/wiki/Q182667","display_name":"Pareto principle","level":2,"score":0.34619998931884766},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.2612000107765198},{"id":"https://openalex.org/C152124472","wikidata":"https://www.wikidata.org/wiki/Q1204361","display_name":"Redundancy (engineering)","level":2,"score":0.25940001010894775},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.2581000030040741}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.30514","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.30514","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2605.30514","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.30514","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16","score":0.5456540584564209}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Machine":[0],"unlearning":[1,76],"evaluation":[2],"is":[3,51,171],"structurally":[4],"skewed:":[5],"Why-type":[6,99,114,184],"questions,":[7],"which":[8],"probe":[9],"causal":[10,41,75,112,185],"and":[11,23,30,48,95,134,165,180],"relational":[12],"knowledge,":[13,105,186],"comprise":[14],"less":[15,24,126],"than":[16,25,127],"0.06%":[17],"of":[18,21,27,122],"CounterFact,":[19],"0.6%":[20],"ZSRE,":[22],"1.3%":[26],"TOFU,":[28],"MUSE,":[29],"WMDP-Cyber.":[31],"This":[32],"near-zero":[33],"representation":[34],"means":[35],"that":[36,38,87],"methods":[37,108],"fail":[39,109],"on":[40,98,152,183,192],"knowledge":[42],"can":[43],"score":[44],"highly":[45],"in":[46],"aggregate,":[47],"this":[49],"failure":[50],"undetectable":[52],"without":[53],"balanced":[54,60],"evaluation.":[55],"We":[56,141,197],"present":[57,142],"5WBENCH,":[58,84],"a":[59,148,188],"5,000-sample":[61],"benchmark":[62],"with":[63],"1,000":[64],"examples":[65],"per":[66],"5W":[67],"category":[68],"(Who,":[69],"What,":[70],"When,":[71],"Where,":[72],"Why),":[73],"making":[74],"failures":[77],"quantifiable":[78],"for":[79,132],"the":[80,172,193],"first":[81,173],"time.":[82],"Using":[83],"we":[85],"show":[86],"no":[88],"existing":[89],"baseline":[90],"simultaneously":[91,176],"achieves":[92],"high":[93,96,178,181],"forgetting":[94,102,179],"retention":[97,182],"questions:":[100],"aggressive":[101],"degrades":[103],"retained":[104],"while":[106],"conservative":[107],"to":[110,130,175],"forget":[111],"facts.":[113],"difficulty":[115],"stems":[116],"from":[117],"multi-hop":[118],"reasoning":[119],"chains":[120],"(44%":[121],"Why":[123],"entries":[124],"vs.":[125],"or":[128],"equal":[129],"2%":[131],"others)":[133],"gradient":[135],"dilution":[136],"over":[137],"40.1-token":[138],"answer":[139],"spans.":[140],"MAAT":[143,170],"(Multi-phase":[144],"Adapter-Aware":[145],"Targeted":[146],"Unlearning),":[147],"three-phase":[149],"framework":[150],"operating":[151,190],"LoRA":[153],"adapter":[154],"weights,":[155],"combining":[156],"gradient-projected":[157],"ascent,":[158],"SVD":[159],"rank-dimension":[160],"pruning,":[161],"task":[162],"vector":[163],"negation,":[164],"hybrid":[166],"KL-hidden-state":[167],"retain":[168],"repair.":[169],"method":[174],"achieve":[177],"reaching":[187],"new":[189],"point":[191],"forget-retain":[194],"Pareto":[195],"frontier.":[196],"make":[198],"our":[199],"code":[200],"publicly":[201],"available.":[202]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-06-02T00:00:00"}
