{"id":"https://openalex.org/W7203674660","doi":"https://doi.org/10.1145/3799682.3840709","title":"RoE-FND: Synergizing LLMs with Experiential Learning for Effective and Generalizable Evidence-Based Fake News Detection","display_name":"RoE-FND: Synergizing LLMs with Experiential Learning for Effective and Generalizable Evidence-Based Fake News Detection","publication_year":2026,"publication_date":"2026-11-03","ids":{"openalex":"https://openalex.org/W7203674660","doi":"https://doi.org/10.1145/3799682.3840709"},"language":"en","primary_location":{"id":"doi:10.1145/3799682.3840709","doi":"https://doi.org/10.1145/3799682.3840709","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3799682.3840709","pdf_url":null,"source":{"id":"https://openalex.org/S4393918199","display_name":"ACM International Conference on Information and Knowledge Management (CIKM)","issn_l":"2155-0751","issn":["2155-0751"],"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"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 35th ACM International Conference on Information and Knowledge Management","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","is_traditional":true,"indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://doi.org/10.1145/3799682.3840709","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5144342305","display_name":"Yuzhou Yang","orcid":"https://orcid.org/0000-0001-6957-7682","observed_orcids":["https://orcid.org/0000-0001-6957-7682"]},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuzhou Yang","raw_affiliation_strings":["Fudan University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0001-6957-7682","affiliations":[{"raw_affiliation_string":"Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5004724820","display_name":"Qichao Ying","orcid":"https://orcid.org/0000-0002-6527-2424","observed_orcids":["https://orcid.org/0000-0002-6527-2424"]},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qichao Ying","raw_affiliation_strings":["Fudan University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0002-6527-2424","affiliations":[{"raw_affiliation_string":"Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5147405820","display_name":"Sheng Li","orcid":"https://orcid.org/0000-0002-7932-9831","observed_orcids":["https://orcid.org/0000-0002-7932-9831"]},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Sheng Li","raw_affiliation_strings":["Fudan University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0002-7932-9831","affiliations":[{"raw_affiliation_string":"Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5147420389","display_name":"Zhiyin Zhu","orcid":"https://orcid.org/0000-0002-1849-3494","observed_orcids":["https://orcid.org/0000-0002-1849-3494"]},"institutions":[{"id":"https://openalex.org/I163340411","display_name":"Hohai University","ror":"https://ror.org/01wd4xt90","country_code":"CN","type":"education","lineage":["https://openalex.org/I163340411"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhiying Zhu","raw_affiliation_strings":["Hohai University, Nanjing, China"],"raw_orcid":"https://orcid.org/0000-0002-1849-3494","affiliations":[{"raw_affiliation_string":"Hohai University, Nanjing, China","institution_ids":["https://openalex.org/I163340411"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136005528","display_name":"Zhenxing Qian","orcid":"https://orcid.org/0000-0002-5224-6374","observed_orcids":["https://orcid.org/0000-0002-5224-6374"]},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhenxing Qian","raw_affiliation_strings":["Fudan University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0002-5224-6374","affiliations":[{"raw_affiliation_string":"Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5147419090","display_name":"Xinpeng Zhang","orcid":"https://orcid.org/0000-0001-5867-1315","observed_orcids":["https://orcid.org/0000-0001-5867-1315"]},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xinpeng Zhang","raw_affiliation_strings":["Fudan University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0001-5867-1315","affiliations":[{"raw_affiliation_string":"Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":7.6728,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":{"value":0.97786325,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"5663","last_page":"5674"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11147","display_name":"Misinformation and Its Impacts","score":1.0,"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"}},"topics":[{"id":"https://openalex.org/T11147","display_name":"Misinformation and Its Impacts","score":1.0,"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/T11644","display_name":"Spam and Phishing Detection","score":9.999999747378752e-05,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T10028","display_name":"Topic Modeling","score":0.0,"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/fake-news-detection","display_name":"fake news detection","score":0.9990000128746033},{"id":"https://openalex.org/keywords/large-language-models","display_name":"large language models","score":0.9769999980926514},{"id":"https://openalex.org/keywords/experiential-learning","display_name":"experiential learning","score":0.8989999890327454},{"id":"https://openalex.org/keywords/self-reflective-learning","display_name":"self-reflective learning","score":0.7310000061988831},{"id":"https://openalex.org/keywords/reasoning-errors","display_name":"reasoning errors","score":0.43799999356269836},{"id":"https://openalex.org/keywords/cross-dataset-generalization","display_name":"cross-dataset generalization","score":0.9139999747276306},{"id":"https://openalex.org/keywords/misinformation","display_name":"misinformation","score":0.3490000069141388},{"id":"https://openalex.org/keywords/adversarial-reasoning","display_name":"adversarial reasoning","score":0.36000001430511475}],"concepts":[{"id":"https://openalex.org/C37228920","wikidata":"https://www.wikidata.org/wiki/Q1307600","display_name":"Experiential learning","level":2,"score":0.5687000155448914},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.5507000088691711},{"id":"https://openalex.org/C2776946740","wikidata":"https://www.wikidata.org/wiki/Q358652","display_name":"Deliberation","level":3,"score":0.5289000272750854},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5174000263214111},{"id":"https://openalex.org/C27158222","wikidata":"https://www.wikidata.org/wiki/Q5532422","display_name":"Generalizability theory","level":2,"score":0.4618000090122223},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.44920000433921814},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.4472000002861023},{"id":"https://openalex.org/C518677369","wikidata":"https://www.wikidata.org/wiki/Q202833","display_name":"Social media","level":2,"score":0.3747999966144562},{"id":"https://openalex.org/C2779756789","wikidata":"https://www.wikidata.org/wiki/Q28549308","display_name":"Fake news","level":2,"score":0.3711000084877014},{"id":"https://openalex.org/C2779267917","wikidata":"https://www.wikidata.org/wiki/Q170028","display_name":"Deception","level":2,"score":0.36640000343322754},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.35839998722076416},{"id":"https://openalex.org/C2780224610","wikidata":"https://www.wikidata.org/wiki/Q1530061","display_name":"Credibility","level":2,"score":0.3495999872684479},{"id":"https://openalex.org/C2776325391","wikidata":"https://www.wikidata.org/wiki/Q6917865","display_name":"Motivated reasoning","level":3,"score":0.3402999937534332},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.33889999985694885},{"id":"https://openalex.org/C79585631","wikidata":"https://www.wikidata.org/wiki/Q431498","display_name":"Confirmation bias","level":2,"score":0.33799999952316284},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3361000120639801},{"id":"https://openalex.org/C59577422","wikidata":"https://www.wikidata.org/wiki/Q10265143","display_name":"False accusation","level":2,"score":0.3255999982357025},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.32499998807907104},{"id":"https://openalex.org/C77805123","wikidata":"https://www.wikidata.org/wiki/Q161272","display_name":"Social psychology","level":1,"score":0.31220000982284546},{"id":"https://openalex.org/C2778689934","wikidata":"https://www.wikidata.org/wiki/Q1313396","display_name":"Headline","level":2,"score":0.30709999799728394},{"id":"https://openalex.org/C180747234","wikidata":"https://www.wikidata.org/wiki/Q23373","display_name":"Cognitive psychology","level":1,"score":0.3037000000476837},{"id":"https://openalex.org/C57098296","wikidata":"https://www.wikidata.org/wiki/Q12021746","display_name":"Interrogative","level":2,"score":0.29919999837875366},{"id":"https://openalex.org/C100521375","wikidata":"https://www.wikidata.org/wiki/Q2015382","display_name":"Competence (human resources)","level":2,"score":0.29899999499320984},{"id":"https://openalex.org/C99377836","wikidata":"https://www.wikidata.org/wiki/Q1661162","display_name":"Indexicality","level":2,"score":0.2858999967575073},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.28519999980926514},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.28200000524520874},{"id":"https://openalex.org/C2776035091","wikidata":"https://www.wikidata.org/wiki/Q7928819","display_name":"Viewpoints","level":2,"score":0.28189998865127563},{"id":"https://openalex.org/C2776552730","wikidata":"https://www.wikidata.org/wiki/Q189656","display_name":"Disinformation","level":3,"score":0.2775999903678894},{"id":"https://openalex.org/C529147693","wikidata":"https://www.wikidata.org/wiki/Q1193236","display_name":"News media","level":2,"score":0.27559998631477356},{"id":"https://openalex.org/C108827166","wikidata":"https://www.wikidata.org/wiki/Q175975","display_name":"Internet privacy","level":1,"score":0.27390000224113464},{"id":"https://openalex.org/C207609745","wikidata":"https://www.wikidata.org/wiki/Q4944086","display_name":"Bootstrapping (finance)","level":2,"score":0.2718999981880188},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.2680000066757202},{"id":"https://openalex.org/C2776990098","wikidata":"https://www.wikidata.org/wiki/Q13579947","display_name":"Misinformation","level":2,"score":0.2671000063419342},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.2667999863624573},{"id":"https://openalex.org/C207390915","wikidata":"https://www.wikidata.org/wiki/Q1230525","display_name":"Divergence (linguistics)","level":2,"score":0.2630000114440918},{"id":"https://openalex.org/C120397944","wikidata":"https://www.wikidata.org/wiki/Q3043314","display_name":"Forbearance","level":2,"score":0.25699999928474426},{"id":"https://openalex.org/C2777375102","wikidata":"https://www.wikidata.org/wiki/Q208351","display_name":"Disgust","level":3,"score":0.2565999925136566},{"id":"https://openalex.org/C79416737","wikidata":"https://www.wikidata.org/wiki/Q2305519","display_name":"Social learning","level":2,"score":0.25609999895095825}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1145/3799682.3840709","doi":"https://doi.org/10.1145/3799682.3840709","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3799682.3840709","pdf_url":null,"source":{"id":"https://openalex.org/S4393918199","display_name":"ACM International Conference on Information and Knowledge Management (CIKM)","issn_l":"2155-0751","issn":["2155-0751"],"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"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 35th ACM International Conference on Information and Knowledge Management","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2608.15210","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2608.15210","pdf_url":"https://arxiv.org/pdf/2608.15210","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2608.15210","doi":"https://doi.org/10.48550/arxiv.2608.15210","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2608.15210","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.1145/3799682.3840709","doi":"https://doi.org/10.1145/3799682.3840709","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3799682.3840709","pdf_url":null,"source":{"id":"https://openalex.org/S4393918199","display_name":"ACM International Conference on Information and Knowledge Management (CIKM)","issn_l":"2155-0751","issn":["2155-0751"],"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"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 35th ACM International Conference on Information and Knowledge Management","raw_type":"proceedings-article"},"sustainable_development_goals":[],"study_designs":[],"awards":[{"id":"https://openalex.org/G4826812297","display_name":null,"funder_award_id":"25ZR1401019","funder_id":"https://openalex.org/F4320309612","funder_display_name":"Natural Science Foundation of Shanghai"},{"id":"https://openalex.org/G5685869395","display_name":null,"funder_award_id":"62572125","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/F4320321543","display_name":"China Postdoctoral Science Foundation","ror":"https://ror.org/0426zh255"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7203674660.pdf","grobid_xml":"https://content.openalex.org/works/W7203674660.grobid-xml"},"referenced_works_count":35,"referenced_works":["https://openalex.org/W2084591134","https://openalex.org/W2594382603","https://openalex.org/W2759820691","https://openalex.org/W2890801081","https://openalex.org/W2950031296","https://openalex.org/W3031781733","https://openalex.org/W3037666784","https://openalex.org/W3093115118","https://openalex.org/W3127495942","https://openalex.org/W3174342531","https://openalex.org/W4221148143","https://openalex.org/W4224324956","https://openalex.org/W4283452667","https://openalex.org/W4288079542","https://openalex.org/W4382131058","https://openalex.org/W4382239959","https://openalex.org/W4382318241","https://openalex.org/W4384918448","https://openalex.org/W4385541615","https://openalex.org/W4385570355","https://openalex.org/W4386172480","https://openalex.org/W4387225871","https://openalex.org/W4393160654","https://openalex.org/W4396723114","https://openalex.org/W4401042753","https://openalex.org/W4401863513","https://openalex.org/W4403791354","https://openalex.org/W4405655184","https://openalex.org/W4405766390","https://openalex.org/W4405903187","https://openalex.org/W4409656984","https://openalex.org/W4411119990","https://openalex.org/W4412923222","https://openalex.org/W4414281281","https://openalex.org/W4416036304"],"related_works":["https://openalex.org/W4415068029","https://openalex.org/W7168170542","https://openalex.org/W4416250438","https://openalex.org/W4393160654","https://openalex.org/W4406421219","https://openalex.org/W4409346770","https://openalex.org/W4388468409","https://openalex.org/W4410172294","https://openalex.org/W4402669683","https://openalex.org/W7131428342"],"abstract_inverted_index":{"The":[0],"proliferation":[1],"of":[2],"deceptive":[3],"content":[4],"in":[5,39],"social":[6],"networks":[7],"necessitates":[8],"robust":[9],"Fake":[10],"News":[11],"Detection":[12],"(FND)":[13],"systems.":[14],"Existing":[15],"pipelines":[16],"either":[17,37],"train":[18],"detectors":[19],"on":[20,64,176],"labeled":[21],"data":[22],"or":[23,41],"leverage":[24],"Large":[25],"Language":[26],"Models":[27],"(LLMs)":[28],"for":[29,80,134],"their":[30,108,136],"reasoning":[31,58,113],"ability.":[32],"However,":[33],"current":[34],"approaches":[35],"remain":[36],"limited":[38],"generalizability":[40],"prone":[42],"to":[43,45,55],"over-commitment":[44],"persuasive":[46],"yet":[47],"flawed":[48],"rationales,":[49],"lacking":[50],"systematic":[51],"experience":[52,73,85],"and":[53,139,160],"mechanisms":[54],"expose":[56],"subtle":[57],"errors.":[59],"We":[60],"propose":[61],"RoE-FND":[62,82,117,168],"(Reason":[63],"Experiences":[65],"FND),":[66],"an":[67,84,92],"LLM-based":[68],"framework":[69],"that":[70,90,167],"combines":[71],"self-reflective":[72],"building":[74],"with":[75,95],"deliberation":[76],"through":[77],"retrieved":[78],"experiences":[79,133],"FND.":[81],"builds":[83],"bank":[86],"via":[87,122],"reflective":[88],"learning":[89],"compares":[91],"unconstrained":[93],"analysis":[94,98],"a":[96,123],"label-conditioned":[97],"using":[99],"the":[100,130,141,145],"ground-truth":[101],"label":[102],"as":[103,127,144],"posterior":[104],"supervision,":[105],"then":[106],"summarizes":[107],"critical":[109],"divergence":[110],"into":[111],"reusable":[112],"guidelines.":[114],"During":[115],"inference,":[116],"generates":[118],"two":[119],"opposing":[120],"deductions":[121],"flipped":[124],"pseudo-label":[125],"provided":[126],"posterior,":[128],"retrieves":[129],"most":[131],"relevant":[132],"resolving":[135],"key":[137],"disagreement,":[138],"adjudicates":[140],"better-supported":[142],"rationale":[143],"final":[146],"prediction.":[147],"Experiments":[148],"across":[149],"five":[150],"popular":[151],"benchmarks,":[152],"including":[153],"text-only":[154],"datasets,":[155,162],"i.e.,":[156,163],"CHEF,":[157],"Snopes,":[158],"PolitiFact,":[159],"multimedia":[161],"FakeTT,":[164],"FakeSV,":[165],"demonstrate":[166],"outperforms":[169],"strong":[170,181],"baselines":[171],"without":[172],"optimizing":[173],"LLM":[174],"parameters":[175],"dataset":[177],"distributions,":[178],"while":[179],"exhibiting":[180],"cross-dataset":[182],"generalization.":[183]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-11-08T12:12:28.789561","created_date":"2026-08-19T00:00:00"}