{"id":"https://openalex.org/W4402670256","doi":"https://doi.org/10.18653/v1/2024.findings-acl.611","title":"Making Harmful Behaviors Unlearnable for Large Language Models","display_name":"Making Harmful Behaviors Unlearnable for Large Language Models","publication_year":2024,"publication_date":"2024-01-01","ids":{"openalex":"https://openalex.org/W4402670256","doi":"https://doi.org/10.18653/v1/2024.findings-acl.611"},"language":"en","primary_location":{"id":"doi:10.18653/v1/2024.findings-acl.611","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2024.findings-acl.611","pdf_url":"https://aclanthology.org/2024.findings-acl.611.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 ACL 2024","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://aclanthology.org/2024.findings-acl.611.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100637499","display_name":"Xin Zhou","orcid":"https://orcid.org/0000-0001-7539-2342"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Xin Zhou","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5111864983","display_name":"Yi Lu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yi Lu","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5107642691","display_name":"Ruotian Ma","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ruotian Ma","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5107568525","display_name":"Yujian Wei","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yujian Wei","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108571703","display_name":"Tao Gui","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tao Gui","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108716441","display_name":"Qi Zhang","orcid":"https://orcid.org/0000-0002-7936-8726"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Qi Zhang","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5107525623","display_name":"Xuanjing Huang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xuanjing Huang","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5100637499"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.3345,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":{"value":0.66016238,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"10258","last_page":"10273"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.7434999942779541,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.7434999942779541,"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/computer-science","display_name":"Computer science","score":0.664328932762146}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.664328932762146}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18653/v1/2024.findings-acl.611","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2024.findings-acl.611","pdf_url":"https://aclanthology.org/2024.findings-acl.611.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 ACL 2024","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.18653/v1/2024.findings-acl.611","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2024.findings-acl.611","pdf_url":"https://aclanthology.org/2024.findings-acl.611.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 ACL 2024","raw_type":"proceedings-article"},"sustainable_development_goals":[{"score":0.46000000834465027,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"}],"awards":[{"id":"https://openalex.org/G655273820","display_name":null,"funder_award_id":"62076069","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7906531246","display_name":null,"funder_award_id":"6207606","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320309612","display_name":"Natural Science Foundation of Shanghai","ror":null},{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320327803","display_name":"Shanghai Rising-Star Program","ror":null},{"id":"https://openalex.org/F4320335796","display_name":"Program of Shanghai Academic Research Leader","ror":null}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4402670256.pdf","grobid_xml":"https://content.openalex.org/works/W4402670256.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052","https://openalex.org/W2382290278","https://openalex.org/W4395014643"],"abstract_inverted_index":{"Large":[0],"language":[1],"models":[2],"(LLMs)":[3],"have":[4],"shown":[5],"great":[6],"potential":[7],"to":[8,34,43,79,92,144,169],"empower":[9],"various":[10],"domains":[11],"and":[12,50,97,124,162],"are":[13,106,142],"often":[14,56],"customized":[15],"by":[16],"fine-tuning":[17,54],"for":[18,129],"the":[19,24,53,85,94,102,110,114,146,153,167],"requirements":[20],"of":[21,28],"different":[22],"applications.However,":[23],"powerful":[25],"learning":[26,44,70,160],"ability":[27,168],"LLMs":[29,65],"not":[30],"only":[31],"enables":[32],"them":[33,41],"learn":[35,170],"new":[36],"tasks":[37],"but":[38],"also":[39],"makes":[40,113],"vulnerable":[42],"undesired":[45,81,103],"behaviors,":[46],"such":[47,61,118],"as":[48,52],"harmfulness":[49],"hallucination,":[51],"data":[55,68,134],"implicitly":[57],"or":[58],"explicitly":[59],"contains":[60],"content.Can":[62],"we":[63,88],"fine-tune":[64],"on":[66],"harmful":[67,71,161],"without":[69],"behaviors?This":[72],"paper":[73,174],"proposes":[74],"a":[75],"controllable":[76],"training":[77],"framework":[78],"make":[80,98],"behaviors":[82],"unlearnable":[83],"during":[84,108],"finetuning":[86],"process.Specifically,":[87],"introduce":[89],"security":[90,140,154],"vectors":[91,105,141,155],"control":[93],"model's":[95],"behavior":[96,112,119,164],"it":[99],"consistent":[100,111],"with":[101],"behavior.Security":[104],"activated":[107],"fine-tuning,":[109,139],"model":[115],"believe":[116],"that":[117,152],"has":[120],"already":[121],"been":[122],"learned":[123],"there":[125],"is":[126],"no":[127],"need":[128],"further":[130],"optimization,":[131],"while":[132,165],"inconsistent":[133],"can":[135,156],"still":[136],"be":[137],"learned.After":[138],"deactivated":[143],"restore":[145],"LLM's":[147],"normal":[148],"behavior.Our":[149],"experiments":[150],"show":[151],"prevent":[157],"LLM":[158],"from":[159],"hallucination":[163],"preserving":[166],"other":[171],"information.Warning:":[172],"This":[173],"may":[175],"contain":[176],"offensive":[177],"content.":[178]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-04-21T08:09:41.155169","created_date":"2025-10-10T00:00:00"}
