{"id":"https://openalex.org/W7166838848","doi":"https://doi.org/10.18653/v1/2026.acl-long.73","title":"Logic Matters in Lightweight Hallucination Classification for RAG System","display_name":"Logic Matters in Lightweight Hallucination Classification for RAG System","publication_year":2026,"publication_date":"2026-01-01","ids":{"openalex":"https://openalex.org/W7166838848","doi":"https://doi.org/10.18653/v1/2026.acl-long.73"},"language":null,"primary_location":{"id":"doi:10.18653/v1/2026.acl-long.73","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2026.acl-long.73","pdf_url":"https://aclanthology.org/2026.acl-long.73.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":"Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://aclanthology.org/2026.acl-long.73.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5139721575","display_name":"Ningyuan Yang","orcid":null},"institutions":[{"id":"https://openalex.org/I4210159968","display_name":"Duke Kunshan University","ror":"https://ror.org/04sr5ys16","country_code":"CN","type":"education","lineage":["https://openalex.org/I170897317","https://openalex.org/I37461747","https://openalex.org/I4210159968"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ningyuan Yang","raw_affiliation_strings":["Duke Kunshan University Duke Kunshan University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Duke Kunshan University Duke Kunshan University","institution_ids":["https://openalex.org/I4210159968"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5139808828","display_name":"Kaizhu Huang","orcid":null},"institutions":[{"id":"https://openalex.org/I4210159968","display_name":"Duke Kunshan University","ror":"https://ror.org/04sr5ys16","country_code":"CN","type":"education","lineage":["https://openalex.org/I170897317","https://openalex.org/I37461747","https://openalex.org/I4210159968"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kaizhu Huang","raw_affiliation_strings":["Duke Kunshan University Duke Kunshan University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Duke Kunshan University Duke Kunshan University","institution_ids":["https://openalex.org/I4210159968"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I4210159968"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.90047022,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1605","last_page":"1617"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12553","display_name":"Psychedelics and Drug Studies","score":0.3707999885082245,"subfield":{"id":"https://openalex.org/subfields/3203","display_name":"Clinical Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T12553","display_name":"Psychedelics and Drug Studies","score":0.3707999885082245,"subfield":{"id":"https://openalex.org/subfields/3203","display_name":"Clinical Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T13397","display_name":"Hallucinations in medical conditions","score":0.10490000247955322,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T13044","display_name":"Biofield Effects and Biophysics","score":0.040699999779462814,"subfield":{"id":"https://openalex.org/subfields/2737","display_name":"Physiology"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.3531999886035919},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.2529999911785126},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.23160000145435333},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.22830000519752502}],"concepts":[{"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":0.4945000112056732},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.3531999886035919},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.33410000801086426},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3147999942302704},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.2529999911785126},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.24220000207424164},{"id":"https://openalex.org/C46312422","wikidata":"https://www.wikidata.org/wiki/Q11024","display_name":"Communication","level":1,"score":0.24130000174045563},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.23160000145435333},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.22830000519752502}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18653/v1/2026.acl-long.73","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2026.acl-long.73","pdf_url":"https://aclanthology.org/2026.acl-long.73.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":"Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.18653/v1/2026.acl-long.73","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2026.acl-long.73","pdf_url":"https://aclanthology.org/2026.acl-long.73.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":"Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1698772872","display_name":null,"funder_award_id":"92370119","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5866557873","display_name":null,"funder_award_id":"62376113","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7166838848.pdf","grobid_xml":"https://content.openalex.org/works/W7166838848.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"We":[0],"propose":[1],"a":[2,64,86,127],"lightweight,":[3],"modular":[4],"framework":[5],"for":[6,136],"hallucination":[7,130],"detection":[8],"in":[9],"Retrieval-Augmented":[10],"Generation":[11],"(RAG)":[12],"systems,":[13],"addressing":[14],"the":[15,32,120],"critical":[16],"challenge":[17],"where":[18],"logical":[19,34],"dependencies":[20],"span":[21],"across":[22,41],"fragmented":[23],"retrieval":[24],"results.Through":[25],"graph-based":[26,114],"semantic":[27],"evidence":[28,115],"aggregation,":[29],"which":[30],"captures":[31],"implicit":[33],"structure":[35],"by":[36,82],"clustering":[37],"semantically":[38],"coherent":[39],"segments":[40],"retrieved":[42,134],"documents":[43,135],"via":[44],"betweenness":[45],"centrality,":[46],"our":[47],"approach":[48],"enables":[49],"small":[50],"NLI":[51,105],"models":[52,107],"to":[53],"handle":[54],"multihop":[55],"reasoning":[56],"without":[57],"task-specific":[58],"training.We":[59],"present":[60],"two":[61],"deployment":[62],"configurations:":[63],"resource-efficient":[65],"variant":[66,88],"(\u22480.5B":[67],"parameters)":[68,90],"achieving":[69],"82.4%":[70],"accuracy":[71],"on":[72],"HotPotQA-Derived":[73],"at":[74],"85":[75],"ms":[76],"latency,":[77],"outperforming":[78],"all":[79],"sub-1B":[80],"baselines":[81],"over":[83],"30%;":[84],"and":[85,100,119],"higheraccuracy":[87],"(\u22481.5B":[89],"reaching":[91],"85.6%,":[92],"surpassing":[93],"11B":[94],"TrueTeacher":[95],"while":[96],"being":[97],"7\u00d7":[98],"smaller":[99],"1.7\u00d7":[101],"faster.Experiments":[102],"with":[103],"six":[104],"discriminator":[106],"show":[108],"consistent":[109],"gains":[110],"of":[111],"+6.7%-+29.9%,confirming":[112],"that":[113],"aggregation":[116],"is":[117],"NLIagnostic":[118],"primary":[121],"performance":[122],"driver.We":[123],"also":[124],"contribute":[125],"HotPotQA-Derived,":[126],"new":[128],"multi-hop":[129],"benchmark":[131],"preserving":[132],"separate":[133],"systematic":[137],"evaluation.":[138]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2026-07-02T00:00:00"}