{"id":"https://openalex.org/W7125136008","doi":"https://doi.org/10.48550/arxiv.2601.12019","title":"Acting Flatterers via LLMs Sycophancy: Combating Clickbait with LLMs Opposing-Stance Reasoning","display_name":"Acting Flatterers via LLMs Sycophancy: Combating Clickbait with LLMs Opposing-Stance Reasoning","publication_year":2026,"publication_date":"2026-01-17","ids":{"openalex":"https://openalex.org/W7125136008","doi":"https://doi.org/10.48550/arxiv.2601.12019"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2601.12019","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2601.12019","pdf_url":null,"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":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2601.12019","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5123497059","display_name":"Chaowei Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Zhang, Chaowei","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101350175","display_name":"Xiansheng Luo","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Luo, Xiansheng","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5123468415","display_name":"Zewei Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Zewei","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5123498104","display_name":"Yi Zhu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhu, Yi","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5123476890","display_name":"Jipeng Qiang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Qiang, Jipeng","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5101616222","display_name":"Longwei Wang","orcid":"https://orcid.org/0000-0003-3001-2953"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Longwei","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5123497059"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11147","display_name":"Misinformation and Its Impacts","score":0.8931999802589417,"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":0.8931999802589417,"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/T10028","display_name":"Topic Modeling","score":0.019500000402331352,"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/T13629","display_name":"Text Readability and Simplification","score":0.009800000116229057,"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/credibility","display_name":"Credibility","score":0.6589000225067139},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.4316999912261963},{"id":"https://openalex.org/keywords/language-model","display_name":"Language model","score":0.4147999882698059},{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.40779998898506165},{"id":"https://openalex.org/keywords/case-based-reasoning","display_name":"Case-based reasoning","score":0.39430001378059387},{"id":"https://openalex.org/keywords/work","display_name":"Work (physics)","score":0.3230000138282776}],"concepts":[{"id":"https://openalex.org/C2780224610","wikidata":"https://www.wikidata.org/wiki/Q1530061","display_name":"Credibility","level":2,"score":0.6589000225067139},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5374000072479248},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.4316999912261963},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.41679999232292175},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.4147999882698059},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.40779998898506165},{"id":"https://openalex.org/C20162079","wikidata":"https://www.wikidata.org/wiki/Q1151406","display_name":"Case-based reasoning","level":2,"score":0.39430001378059387},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.3476000130176544},{"id":"https://openalex.org/C18762648","wikidata":"https://www.wikidata.org/wiki/Q42213","display_name":"Work (physics)","level":2,"score":0.3230000138282776},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.3192000091075897},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.31459999084472656},{"id":"https://openalex.org/C77805123","wikidata":"https://www.wikidata.org/wiki/Q161272","display_name":"Social psychology","level":1,"score":0.30250000953674316},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.2847000062465668},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.2703999876976013},{"id":"https://openalex.org/C180747234","wikidata":"https://www.wikidata.org/wiki/Q23373","display_name":"Cognitive psychology","level":1,"score":0.26600000262260437},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.25870001316070557},{"id":"https://openalex.org/C188147891","wikidata":"https://www.wikidata.org/wiki/Q147638","display_name":"Cognitive science","level":1,"score":0.25619998574256897},{"id":"https://openalex.org/C195344581","wikidata":"https://www.wikidata.org/wiki/Q2555318","display_name":"Automated reasoning","level":2,"score":0.2533999979496002},{"id":"https://openalex.org/C2780791683","wikidata":"https://www.wikidata.org/wiki/Q846785","display_name":"Action (physics)","level":2,"score":0.25270000100135803}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2601.12019","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2601.12019","pdf_url":null,"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":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2601.12019","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2601.12019","pdf_url":null,"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":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"The":[0,142],"widespread":[1],"proliferation":[2],"of":[3],"online":[4],"content":[5],"has":[6],"intensified":[7],"concerns":[8],"about":[9],"clickbait,":[10],"deceptive":[11],"or":[12],"exaggerated":[13],"headlines":[14],"designed":[15],"to":[16,41,63,77,97,134,156],"attract":[17],"attention.":[18],"While":[19],"Large":[20],"Language":[21],"Models":[22],"(LLMs)":[23],"offer":[24],"a":[25,39,61,69,87,106,121],"promising":[26],"avenue":[27],"for":[28,105],"addressing":[29],"this":[30,66,75],"issue,":[31],"their":[32],"effectiveness":[33],"is":[34],"often":[35],"hindered":[36],"by":[37,148],"Sycophancy,":[38],"tendency":[40],"produce":[42,98],"reasoning":[43,80,103],"that":[44,72,94,129,167],"matches":[45],"users'":[46],"beliefs":[47],"over":[48],"truthful":[49],"ones,":[50],"which":[51],"deviates":[52],"from":[53,81,152],"instruction-following":[54],"principles.":[55],"Rather":[56],"than":[57],"treating":[58],"sycophancy":[59],"as":[60],"flaw":[62],"be":[64],"eliminated,":[65],"work":[67],"proposes":[68],"novel":[70],"approach":[71],"initially":[73],"harnesses":[74],"behavior":[76],"generate":[78],"contrastive":[79,145],"opposing":[82],"perspectives.":[83],"Specifically,":[84],"we":[85,119],"design":[86],"Self-renewal":[88],"Opposing-stance":[89],"Reasoning":[90],"Generation":[91],"(SORG)":[92],"framework":[93],"prompts":[95],"LLMs":[96],"high-quality":[99],"agree":[100],"and":[101,138,178],"disagree":[102],"pairs":[104],"given":[107],"news":[108],"title":[109,137],"without":[110],"requiring":[111],"ground-truth":[112],"labels.":[113],"To":[114],"utilize":[115],"the":[116,136],"generated":[117],"reasoning,":[118],"develop":[120],"local":[122],"Opposing":[123],"Reasoning-based":[124],"Clickbait":[125],"Detection":[126],"(ORCD)":[127],"model":[128,143],"integrates":[130],"three":[131,163],"BERT":[132],"encoders":[133],"represent":[135],"its":[139],"associated":[140],"reasoning.":[141],"leverages":[144],"learning,":[146],"guided":[147],"soft":[149],"labels":[150],"derived":[151],"LLM-generated":[153],"credibility":[154],"scores,":[155],"enhance":[157],"detection":[158,181],"robustness.":[159],"Experimental":[160],"evaluations":[161],"on":[162],"benchmark":[164],"datasets":[165],"demonstrate":[166],"our":[168],"method":[169],"consistently":[170],"outperforms":[171],"LLM":[172],"prompting,":[173],"fine-tuned":[174],"smaller":[175],"language":[176],"models,":[177],"state-of-the-art":[179],"clickbait":[180],"baselines.":[182]},"counts_by_year":[],"updated_date":"2026-01-22T23:33:04.759266","created_date":"2026-01-22T00:00:00"}