{"id":"https://openalex.org/W7152518262","doi":"https://doi.org/10.1145/3774904.3792285","title":"A Fact-Checking Framework with Denoising Evidence Retrieval and LLM-Based Debate Verification","display_name":"A Fact-Checking Framework with Denoising Evidence Retrieval and LLM-Based Debate Verification","publication_year":2026,"publication_date":"2026-04-09","ids":{"openalex":"https://openalex.org/W7152518262","doi":"https://doi.org/10.1145/3774904.3792285"},"language":null,"primary_location":{"id":"doi:10.1145/3774904.3792285","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3774904.3792285","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the ACM Web Conference 2026","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Jun Yang","orcid":"https://orcid.org/0009-0007-2188-0763"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jun Yang","raw_affiliation_strings":["School of Computer Science and Technology, Beijing Institute of Technology, Beijing, Beijing, China"],"raw_orcid":"https://orcid.org/0009-0007-2188-0763","affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Beijing Institute of Technology, Beijing, Beijing, China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Yuhan Bai","orcid":"https://orcid.org/0009-0005-3842-1390"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuhan Bai","raw_affiliation_strings":["School of Computer Science and Technology, Beijing Institute of Technology, Beijing, Beijing, China"],"raw_orcid":"https://orcid.org/0009-0005-3842-1390","affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Beijing Institute of Technology, Beijing, Beijing, China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129705791","display_name":"Dandan Song","orcid":null},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dandan Song","raw_affiliation_strings":["School of Computer Science and Technology, Beijing Institute of Technology, Beijing, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-7239-6900","affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Beijing Institute of Technology, Beijing, Beijing, China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Zhijing Wu","orcid":"https://orcid.org/0000-0003-2473-3746"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhijing Wu","raw_affiliation_strings":["School of Computer Science and Technology, Beijing Institute of Technology, Beijing, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0003-2473-3746","affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Beijing Institute of Technology, Beijing, Beijing, China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5075296505","display_name":"Yuhang Tian","orcid":"https://orcid.org/0009-0000-4726-9427"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuhang Tian","raw_affiliation_strings":["School of Computer Science and Technology, Beijing Institute of Technology, Beijing, Beijing, China"],"raw_orcid":"https://orcid.org/0009-0000-4726-9427","affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Beijing Institute of Technology, Beijing, Beijing, China","institution_ids":["https://openalex.org/I125839683"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.51754909,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"2094","last_page":"2104"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.33719998598098755,"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":0.33719998598098755,"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":0.16940000653266907,"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"}},{"id":"https://openalex.org/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.052799999713897705,"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/noise","display_name":"Noise (video)","score":0.32280001044273376},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3122999966144562},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.3089999854564667},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.2971000075340271}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6025000214576721},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5400000214576721},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3734999895095825},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.32280001044273376},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.31859999895095825},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3122999966144562},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.3089999854564667},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.2971000075340271},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.2524000108242035},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.25049999356269836}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3774904.3792285","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3774904.3792285","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the ACM Web Conference 2026","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":42,"referenced_works":["https://openalex.org/W1546111015","https://openalex.org/W2291868768","https://openalex.org/W2618530766","https://openalex.org/W2741930413","https://openalex.org/W2742330194","https://openalex.org/W2743800013","https://openalex.org/W2759820691","https://openalex.org/W2889787757","https://openalex.org/W2892163801","https://openalex.org/W2950031296","https://openalex.org/W2963961878","https://openalex.org/W2964068236","https://openalex.org/W3014820715","https://openalex.org/W3034828027","https://openalex.org/W3168659546","https://openalex.org/W3174342531","https://openalex.org/W3174691662","https://openalex.org/W3175971736","https://openalex.org/W3194769714","https://openalex.org/W3196268181","https://openalex.org/W4200069439","https://openalex.org/W4283452667","https://openalex.org/W4385570272","https://openalex.org/W4385570355","https://openalex.org/W4385570504","https://openalex.org/W4385570777","https://openalex.org/W4385571813","https://openalex.org/W4386576876","https://openalex.org/W4389518962","https://openalex.org/W4389520455","https://openalex.org/W4392637187","https://openalex.org/W4393160654","https://openalex.org/W4393160773","https://openalex.org/W4401023575","https://openalex.org/W4401042272","https://openalex.org/W4404534210","https://openalex.org/W4409159827","https://openalex.org/W4409362488","https://openalex.org/W4410088531","https://openalex.org/W4411119657","https://openalex.org/W4416037237","https://openalex.org/W6948412671"],"related_works":[],"abstract_inverted_index":{"The":[0],"rapid":[1],"spread":[2],"of":[3,12,48,99,105],"misinformation":[4],"on":[5,20,137],"social":[6],"media":[7],"has":[8],"underscored":[9],"the":[10,37,46,49,55,87,103,109,114,146],"importance":[11],"automatic":[13],"fact-checking.":[14],"Existing":[15],"fact-checking":[16,74],"pipelines":[17],"typically":[18],"rely":[19],"multi-stage":[21],"frameworks":[22],"involving":[23],"evidence":[24,80],"retrieval":[25,38,81,88],"and":[26,53,82,97,120,139],"claim":[27],"verification.":[28,85],"However,":[29],"these":[30,69],"methods":[31],"face":[32],"two":[33],"major":[34],"challenges:":[35],"(1)":[36],"process":[39],"often":[40],"introduces":[41],"noisy":[42,106],"evidence,":[43,101],"which":[44],"compromises":[45],"reliability":[47],"final":[50,133],"veracity":[51,134],"prediction;":[52],"(2)":[54],"verification":[56,110,152],"models":[57],"may":[58],"overlook":[59],"critical":[60],"factual":[61],"details,":[62],"resulting":[63],"in":[64,149],"hallucinated":[65],"conclusions.":[66],"To":[67],"address":[68],"issues,":[70],"we":[71],"propose":[72],"a":[73,122,129],"framework":[75],"SLED":[76,90,112,144],"with":[77],"Self-supervised":[78],"denoising":[79],"LLM-Enhanced":[83],"Debate-based":[84],"In":[86,108],"stage,":[89,111],"leverage":[91],"trained":[92],"verifier":[93],"to":[94,116],"assess":[95],"credibility":[96],"necessity":[98],"retrieved":[100],"enabling":[102],"elimination":[104],"evidence.":[107],"prompts":[113],"LLM":[115],"generate":[117],"dual-perspective":[118],"reasoning":[119],"simulates":[121],"multi-agent":[123],"debate,":[124],"followed":[125],"by":[126],"distillation":[127],"into":[128],"lightweight":[130],"model":[131],"for":[132],"prediction.":[135],"Experiments":[136],"CHEF":[138],"HOVER":[140],"datasets":[141],"demonstrate":[142],"that":[143],"achieves":[145],"state-of-the-art":[147],"results":[148],"complex":[150],"fact":[151],"scenarios.":[153]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-04-10T00:00:00"}
