{"id":"https://openalex.org/W7204887032","doi":"https://doi.org/10.48550/arxiv.2608.28623","title":"Talked Out of the Truth: Sycophancy in the Reasoning Chains of Multimodal Models","display_name":"Talked Out of the Truth: Sycophancy in the Reasoning Chains of Multimodal Models","publication_year":2026,"publication_date":"2026-07-30","ids":{"openalex":"https://openalex.org/W7204887032","doi":"https://doi.org/10.48550/arxiv.2608.28623"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2608.28623","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2608.28623","pdf_url":"https://arxiv.org/pdf/2608.28623","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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"volume":null,"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2608.28623","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5148901863","display_name":"Mahir Numayeer Islam","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I4405259444","display_name":"Adelaide University","ror":"https://ror.org/028g18b61","country_code":"AU","type":"education","lineage":["https://openalex.org/I4405259444"]},{"id":"https://openalex.org/I5681781","display_name":"The University of Adelaide","ror":"https://ror.org/00892tw58","country_code":"AU","type":"education","lineage":["https://openalex.org/I4405259444","https://openalex.org/I5681781"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Islam, Mahir Numayeer","raw_affiliation_strings":["Adelaide University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Adelaide University","institution_ids":["https://openalex.org/I4405259444","https://openalex.org/I5681781"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5148938266","display_name":"Gakuto Okuyama","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I70999451","display_name":"Akita International University","ror":"https://ror.org/05qz4zw08","country_code":"JP","type":"education","lineage":["https://openalex.org/I70999451"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Okuyama, Gakuto","raw_affiliation_strings":["Akita International University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Akita International University","institution_ids":["https://openalex.org/I70999451"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5148855849","display_name":"Nikolaus Siauw","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Siauw, Nikolaus","raw_affiliation_strings":["Tech"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tech","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101382789","display_name":"Shivank Garg","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Garg, Shivank","raw_affiliation_strings":["Algoverse AI Research"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Algoverse AI Research","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014668625","display_name":"Madhur Panwar","orcid":"https://orcid.org/0000-0002-0053-733X","observed_orcids":["https://orcid.org/0000-0002-0053-733X"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Panwar, Madhur","raw_affiliation_strings":["Algoverse AI Research"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Algoverse AI Research","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102320649","display_name":"Vasu Sharma","orcid":"https://orcid.org/0009-0006-4348-7412","observed_orcids":["https://orcid.org/0009-0006-4348-7412"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sharma, Vasu","raw_affiliation_strings":["PocketFM & Algoverse AI Research"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"PocketFM & Algoverse AI Research","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9721999764442444,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9721999764442444,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.006599999964237213,"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/T10028","display_name":"Topic Modeling","score":0.002199999988079071,"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/sycophancy","display_name":"sycophancy","score":0.9980000257492065},{"id":"https://openalex.org/keywords/multimodal-large-language-models","display_name":"multimodal large language models","score":0.7020000219345093},{"id":"https://openalex.org/keywords/chain-of-thought-reasoning","display_name":"chain-of-thought reasoning","score":0.9639999866485596},{"id":"https://openalex.org/keywords/visual-grounding","display_name":"visual grounding","score":0.5139999985694885},{"id":"https://openalex.org/keywords/failure-taxonomy","display_name":"failure taxonomy","score":0.753000020980835},{"id":"https://openalex.org/keywords/multi-turn-reasoning","display_name":"multi-turn reasoning","score":0.5270000100135803},{"id":"https://openalex.org/keywords/mathematical-reasoning","display_name":"mathematical reasoning","score":0.6859999895095825},{"id":"https://openalex.org/keywords/temporal-reasoning","display_name":"temporal reasoning","score":0.8529999852180481}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6283000111579895},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6225000023841858},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5935999751091003},{"id":"https://openalex.org/C58642233","wikidata":"https://www.wikidata.org/wiki/Q8269924","display_name":"Taxonomy (biology)","level":2,"score":0.5220999717712402},{"id":"https://openalex.org/C2777508537","wikidata":"https://www.wikidata.org/wiki/Q7936620","display_name":"Visual reasoning","level":2,"score":0.5095999836921692},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.4404999911785126},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.43869999051094055},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4251999855041504},{"id":"https://openalex.org/C100776233","wikidata":"https://www.wikidata.org/wiki/Q2532492","display_name":"Bridge (graph theory)","level":2,"score":0.39340001344680786},{"id":"https://openalex.org/C20162079","wikidata":"https://www.wikidata.org/wiki/Q1151406","display_name":"Case-based reasoning","level":2,"score":0.34369999170303345},{"id":"https://openalex.org/C89288958","wikidata":"https://www.wikidata.org/wiki/Q7301504","display_name":"Reasoning system","level":2,"score":0.32919999957084656},{"id":"https://openalex.org/C97364631","wikidata":"https://www.wikidata.org/wiki/Q484284","display_name":"Deductive reasoning","level":2,"score":0.3260999917984009},{"id":"https://openalex.org/C2777026412","wikidata":"https://www.wikidata.org/wiki/Q2684591","display_name":"Statement (logic)","level":2,"score":0.31150001287460327},{"id":"https://openalex.org/C37335422","wikidata":"https://www.wikidata.org/wiki/Q6888134","display_name":"Model-based reasoning","level":3,"score":0.3019999861717224},{"id":"https://openalex.org/C83725634","wikidata":"https://www.wikidata.org/wiki/Q7268699","display_name":"Qualitative reasoning","level":2,"score":0.29190000891685486},{"id":"https://openalex.org/C195344581","wikidata":"https://www.wikidata.org/wiki/Q2555318","display_name":"Automated reasoning","level":2,"score":0.2531999945640564}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2608.28623","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2608.28623","pdf_url":"https://arxiv.org/pdf/2608.28623","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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2608.28623","doi":"https://doi.org/10.48550/arxiv.2608.28623","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2608.28623","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":"pmh:oai:arXiv.org:2608.28623","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2608.28623","pdf_url":"https://arxiv.org/pdf/2608.28623","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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7204887032.pdf","grobid_xml":"https://content.openalex.org/works/W7204887032.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W7105202865","https://openalex.org/W7208431892","https://openalex.org/W7126195212","https://openalex.org/W7166833852","https://openalex.org/W7220991088","https://openalex.org/W7119501863","https://openalex.org/W7172438735","https://openalex.org/W4416036025","https://openalex.org/W6947989429","https://openalex.org/W7223299335"],"abstract_inverted_index":{"Large":[0],"multimodal":[1],"reasoning":[2,13,76,95,165,180,196],"models":[3,19,115],"(LMRMs)":[4],"are":[5],"increasingly":[6],"capable,":[7],"largely":[8],"through":[9],"generating":[10],"explicit":[11],"chain-of-thought":[12],"before":[14],"answering,":[15],"but":[16,194],"in":[17,42,81,88,126],"language":[18],"this":[20,48],"often":[21],"comes":[22],"with":[23,29,50,77,185],"sycophancy,":[24,145],"the":[25,30,33,89,94,105,111,131,175,178,192,195,201],"tendency":[26],"to":[27,39],"agree":[28],"user":[31,60],"over":[32],"evidence,":[34],"and":[35,53,74,83,92,108,118,146],"no":[36],"reliable":[37],"method":[38],"measure":[40],"it":[41],"LMRMs":[43],"yet":[44],"exists.":[45],"We":[46,135],"bridge":[47],"gap":[49],"a":[51,59,62,138,161],"benchmark":[52],"dataset":[54],"for":[55,113,130],"LMRM":[56],"sycophancy":[57,123,188],"when":[58],"asserts":[61],"wrong":[63],"answer,":[64],"pairing":[65],"four":[66],"visually":[67],"grounded":[68],"datasets":[69],"spanning":[70],"mathematical,":[71],"clinical,":[72],"temporal,":[73],"demographic":[75],"five":[78],"pressure":[79,103,121],"conditions":[80],"single-turn":[82],"multi-turn":[84,120],"settings,":[85],"scored":[86],"both":[87],"final":[90],"answer":[91,176,193],"within":[93],"chain.":[96],"Sycophancy":[97],"is":[98,204],"prevalent":[99],"under":[100,119],"pressure:":[101],"Statement":[102],"elicits":[104],"highest":[106],"rates":[107],"Conviction":[109],"among":[110],"lowest":[112],"all":[114],"except":[116],"Mistral-Small-4,":[117],"reasoning-level":[122],"intensifies":[124],"sharply":[125],"PathVQA,":[127],"reaching":[128],"95.7%":[129],"most":[132],"affected":[133],"model.":[134],"further":[136],"introduce":[137],"failure":[139],"taxonomy":[140,150],"separating":[141],"reasoning-chain":[142],"from":[143],"answer-level":[144],"an":[147],"exploratory":[148],"sentence-level":[149],"locating":[151],"where":[152],"drift":[153],"first":[154],"emerges.":[155],"A":[156],"targeted":[157],"intervention":[158],"that":[159,197],"restores":[160],"model's":[162],"own":[163],"correct":[164],"recovers":[166],"79.2%":[167],"of":[168],"sycophantic":[169,179],"answers":[170],"on":[171],"reasoning-heavy":[172],"tasks,":[173],"showing":[174],"follows":[177],"rather":[181],"than":[182],"merely":[183],"co-occurring":[184],"it.":[186],"Thus,":[187],"corrupts":[189],"not":[190],"just":[191],"produces":[198],"it,":[199],"so":[200],"chain":[202],"itself":[203],"what":[205],"we":[206],"must":[207],"measure.":[208]},"counts_by_year":[],"updated_date":"2026-10-28T10:33:24.094632","created_date":"2026-09-02T00:00:00"}
