{"id":"https://openalex.org/W4403585433","doi":"https://doi.org/10.48550/arxiv.2408.12325","title":"Improving Factuality in Large Language Models via Decoding-Time\n Hallucinatory and Truthful Comparators","display_name":"Improving Factuality in Large Language Models via Decoding-Time\n Hallucinatory and Truthful Comparators","publication_year":2024,"publication_date":"2024-08-22","ids":{"openalex":"https://openalex.org/W4403585433","doi":"https://doi.org/10.48550/arxiv.2408.12325"},"language":"en","primary_location":{"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2408.12325","pdf_url":"http://arxiv.org/pdf/2408.12325","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":["Cornell University"],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false},"type":"preprint","type_crossref":"posted-content","indexed_in":["arxiv"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"http://arxiv.org/pdf/2408.12325","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5064280715","display_name":"Dingkang Yang","orcid":"https://orcid.org/0000-0003-1829-5671"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yang, Dingkang","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5111162223","display_name":"Dongling Xiao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xiao, Dongling","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100586103","display_name":"Jinjie Wei","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wei, Jinjie","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058367079","display_name":"M. H. Li","orcid":"https://orcid.org/0009-0000-6244-6081"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Mingcheng","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101729649","display_name":"Zhaoyu Chen","orcid":"https://orcid.org/0000-0002-7112-2596"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Zhaoyu","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102020099","display_name":"Ke Li","orcid":"https://orcid.org/0000-0002-2236-6578"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Ke","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5100414914","display_name":"Lihua Zhang","orcid":"https://orcid.org/0009-0005-4150-711X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Lihua","raw_affiliation_strings":[],"affiliations":[]}],"institution_assertions":[],"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":{"value":0.0,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":0,"max":83},"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9956,"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":0.9956,"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":0.9673,"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/T11147","display_name":"Misinformation and Its Impacts","score":0.9662,"subfield":{"id":"https://openalex.org/subfields/3312","display_name":"Sociology and Political Science"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[],"concepts":[{"id":"https://openalex.org/C155745195","wikidata":"https://www.wikidata.org/wiki/Q1164179","display_name":"Comparator","level":3,"score":0.80904067},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.80880296},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.53630036},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.34922993},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.34207666},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.1840347},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.11785409},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.078837425},{"id":"https://openalex.org/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2408.12325","pdf_url":"http://arxiv.org/pdf/2408.12325","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":["Cornell University"],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false}],"best_oa_location":{"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2408.12325","pdf_url":"http://arxiv.org/pdf/2408.12325","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":["Cornell University"],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false},"sustainable_development_goals":[],"grants":[],"datasets":[],"versions":[],"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W4366783034","https://openalex.org/W4313221225","https://openalex.org/W3004219868","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2150642609","https://openalex.org/W2034349229","https://openalex.org/W2005410346","https://openalex.org/W1972415042"],"abstract_inverted_index":{"Despite":[0],"their":[1],"remarkable":[2],"capabilities,":[3],"Large":[4],"Language":[5],"Models":[6],"(LLMs)":[7],"are":[8],"prone":[9],"to":[10,69,97,105,120],"generate":[11],"responses":[12],"that":[13,142],"contradict":[14],"verifiable":[15],"facts,":[16],"i.e.,":[17],"unfaithful":[18],"hallucination":[19,108],"content.":[20],"Existing":[21],"efforts":[22],"generally":[23],"focus":[24],"on":[25,137],"optimizing":[26],"model":[27,149],"parameters":[28],"or":[29,109],"editing":[30],"semantic":[31],"representations,":[32],"which":[33],"compromise":[34],"the":[35,53,71,99,102,125,129,148],"internal":[36],"factual":[37],"knowledge":[38],"of":[39,94,101],"target":[40,130],"LLMs.":[41],"In":[42,59,85],"addition,":[43],"hallucinations":[44],"typically":[45],"exhibit":[46],"multifaceted":[47],"patterns":[48,111],"in":[49,112],"downstream":[50,139],"tasks,":[51],"limiting":[52],"model's":[54],"holistic":[55],"performance":[56,150],"across":[57],"tasks.":[58],"this":[60,86],"paper,":[61],"we":[62,75,88],"propose":[63],"a":[64],"Comparator-driven":[65],"Decoding-Time":[66],"(CDT)":[67],"framework":[68,144],"alleviate":[70],"response":[72,152],"hallucination.":[73],"Firstly,":[74],"construct":[76],"hallucinatory":[77],"and":[78,132,151],"truthful":[79],"comparators":[80,104],"with":[81],"multi-task":[82],"fine-tuning":[83],"samples.":[84],"case,":[87],"present":[89],"an":[90],"instruction":[91],"prototype-guided":[92],"mixture":[93],"experts":[95],"strategy":[96],"enhance":[98],"ability":[100],"corresponding":[103],"capture":[106],"different":[107],"truthfulness":[110],"distinct":[113],"task":[114],"instructions.":[115],"CDT":[116],"constrains":[117],"next-token":[118],"predictions":[119],"factuality-robust":[121],"distributions":[122],"by":[123],"contrasting":[124],"logit":[126],"differences":[127],"between":[128],"LLMs":[131],"these":[133],"comparators.":[134],"Systematic":[135],"experiments":[136],"multiple":[138],"tasks":[140],"show":[141],"our":[143],"can":[145],"significantly":[146],"improve":[147],"factuality.":[153]},"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W4403585433","counts_by_year":[],"updated_date":"2025-01-07T16:44:34.414813","created_date":"2024-10-21"}