{"id":"https://openalex.org/W4416034037","doi":"https://doi.org/10.18653/v1/2025.findings-emnlp.774","title":"Human-Inspired Obfuscation for Model Unlearning: Local and Global Strategies with Hyperbolic Representations","display_name":"Human-Inspired Obfuscation for Model Unlearning: Local and Global Strategies with Hyperbolic Representations","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4416034037","doi":"https://doi.org/10.18653/v1/2025.findings-emnlp.774"},"language":null,"primary_location":{"id":"doi:10.18653/v1/2025.findings-emnlp.774","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2025.findings-emnlp.774","pdf_url":"https://aclanthology.org/2025.findings-emnlp.774.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Findings of the Association for Computational Linguistics: EMNLP 2025","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://aclanthology.org/2025.findings-emnlp.774.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100776739","display_name":"Zekun Wang","orcid":"https://orcid.org/0000-0002-4760-3074"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zekun Wang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102532881","display_name":"Jingjie Zeng","orcid":"https://orcid.org/0009-0002-5412-2348"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jingjie Zeng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5049931007","display_name":"Y.-H. Audrey Li","orcid":"https://orcid.org/0009-0001-4803-3712"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yingxu Li","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057791685","display_name":"Liang Huai Yang","orcid":"https://orcid.org/0000-0002-4297-4845"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liang Yang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5101561232","display_name":"Hongfei Lin","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hongfei Lin","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":true,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"14354","last_page":"14366"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11206","display_name":"Model Reduction and Neural Networks","score":0.27059999108314514,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11206","display_name":"Model Reduction and Neural Networks","score":0.27059999108314514,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12072","display_name":"Machine Learning and Algorithms","score":0.0714000016450882,"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":0.03889999911189079,"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/obfuscation","display_name":"Obfuscation","score":0.37540000677108765},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.3698999881744385},{"id":"https://openalex.org/keywords/intersection","display_name":"Intersection (aeronautics)","score":0.288100004196167},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.28439998626708984},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.2752000093460083},{"id":"https://openalex.org/keywords/face","display_name":"Face (sociological concept)","score":0.26809999346733093}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.49230000376701355},{"id":"https://openalex.org/C40305131","wikidata":"https://www.wikidata.org/wiki/Q2616305","display_name":"Obfuscation","level":2,"score":0.37540000677108765},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.37380000948905945},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.3698999881744385},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3517000079154968},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3174999952316284},{"id":"https://openalex.org/C64543145","wikidata":"https://www.wikidata.org/wiki/Q162942","display_name":"Intersection (aeronautics)","level":2,"score":0.288100004196167},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.28439998626708984},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2793000042438507},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.2752000093460083},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.26809999346733093},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.26600000262260437},{"id":"https://openalex.org/C2776036281","wikidata":"https://www.wikidata.org/wiki/Q48769818","display_name":"Constraint (computer-aided design)","level":2,"score":0.2596000134944916},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.25769999623298645},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.2542000114917755}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18653/v1/2025.findings-emnlp.774","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2025.findings-emnlp.774","pdf_url":"https://aclanthology.org/2025.findings-emnlp.774.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Findings of the Association for Computational Linguistics: EMNLP 2025","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.18653/v1/2025.findings-emnlp.774","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2025.findings-emnlp.774","pdf_url":"https://aclanthology.org/2025.findings-emnlp.774.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Findings of the Association for Computational Linguistics: EMNLP 2025","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4416034037.pdf","grobid_xml":"https://content.openalex.org/works/W4416034037.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Large":[0],"language":[1,104],"models":[2,103],"(LLMs)":[3],"achieve":[4],"remarkable":[5],"performance":[6],"across":[7],"various":[8],"domains,":[9],"largely":[10],"due":[11],"to":[12,39,65,86],"training":[13],"on":[14,79],"massive":[15],"datasets.However,":[16],"this":[17,47],"also":[18],"raises":[19],"growing":[20],"concerns":[21],"over":[22],"the":[23,102],"exposure":[24],"of":[25,59],"sensitive":[26,98],"and":[27,63,68,73,89,107,116],"private":[28],"information,":[29],"making":[30],"model":[31,45,81],"unlearning":[32,54],"increasingly":[33],"critical.However,":[34],"existing":[35],"methods":[36],"often":[37],"struggle":[38],"balance":[40],"effective":[41],"forgetting":[42,88,115],"with":[43,82],"maintaining":[44,101],"utility.In":[46],"work,":[48],"we":[49],"propose":[50],"HyperUnlearn,":[51],"a":[52,80,111],"human-inspired":[53],"framework.We":[55],"construct":[56],"two":[57],"types":[58],"fuzzy":[60],"data":[61],"local":[62],"global":[64],"simulate":[66],"forgetting,":[67],"represent":[69],"them":[70],"in":[71],"hyperbolic":[72],"Euclidean":[74],"spaces,":[75],"respectively.Unlearning":[76],"is":[77],"performed":[78],"frozen":[83],"early":[84],"layers":[85],"isolate":[87],"preserve":[90],"useful":[91],"knowledge.Experiments":[92],"demonstrate":[93],"that":[94],"Hy-perUnlearn":[95],"effectively":[96],"forgets":[97],"content":[99],"while":[100],"understanding,":[105],"fluency,":[106],"benchmark":[108],"performance,":[109],"offering":[110],"practical":[112],"trade-off":[113],"between":[114],"capability":[117],"preservation.":[118]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-11-08T00:00:00"}
