{"id":"https://openalex.org/W7128770595","doi":"https://doi.org/10.48550/arxiv.2602.11364","title":"The Energy of Falsehood: Detecting Hallucinations via Diffusion Model Likelihoods","display_name":"The Energy of Falsehood: Detecting Hallucinations via Diffusion Model Likelihoods","publication_year":2026,"publication_date":"2026-02-11","ids":{"openalex":"https://openalex.org/W7128770595","doi":"https://doi.org/10.48550/arxiv.2602.11364"},"language":null,"primary_location":{"id":"pmh:doi:10.48550/arxiv.2602.11364","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"publisher-specific-oa","license_id":"https://openalex.org/licenses/publisher-specific-oa","version":"submittedVersion","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":null,"any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5091549332","display_name":"Arpit Singh Gautam","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Gautam, Arpit Singh","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5125912224","display_name":"Kailash Talreja","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Talreja, Kailash","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5125962135","display_name":"Saurabh Kumar Jha","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jha, Saurabh","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5091549332"],"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.357699990272522,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.357699990272522,"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":0.1080000028014183,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.10189999639987946,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.6777999997138977},{"id":"https://openalex.org/keywords/hallucinating","display_name":"Hallucinating","score":0.6305000185966492},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.5514000058174133},{"id":"https://openalex.org/keywords/generative-model","display_name":"Generative model","score":0.5489000082015991},{"id":"https://openalex.org/keywords/stability","display_name":"Stability (learning theory)","score":0.48649999499320984},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4458000063896179},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.44530001282691956},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.430400013923645},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.4259999990463257}],"concepts":[{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.6777999997138977},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.660099983215332},{"id":"https://openalex.org/C2911011789","wikidata":"https://www.wikidata.org/wiki/Q130741","display_name":"Hallucinating","level":2,"score":0.6305000185966492},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6269000172615051},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.5514000058174133},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.5489000082015991},{"id":"https://openalex.org/C112972136","wikidata":"https://www.wikidata.org/wiki/Q7595718","display_name":"Stability (learning theory)","level":2,"score":0.48649999499320984},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4458000063896179},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.44530001282691956},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.430400013923645},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.4259999990463257},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.40230000019073486},{"id":"https://openalex.org/C207390915","wikidata":"https://www.wikidata.org/wiki/Q1230525","display_name":"Divergence (linguistics)","level":2,"score":0.3758000135421753},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3449999988079071},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3391999900341034},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.3343999981880188},{"id":"https://openalex.org/C529865628","wikidata":"https://www.wikidata.org/wiki/Q1790740","display_name":"Manifold (fluid mechanics)","level":2,"score":0.3156999945640564},{"id":"https://openalex.org/C186370098","wikidata":"https://www.wikidata.org/wiki/Q442787","display_name":"Energy (signal processing)","level":2,"score":0.31209999322891235},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3066999912261963},{"id":"https://openalex.org/C55128770","wikidata":"https://www.wikidata.org/wiki/Q5275440","display_name":"Diffusion map","level":4,"score":0.30640000104904175},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.30559998750686646},{"id":"https://openalex.org/C96442724","wikidata":"https://www.wikidata.org/wiki/Q242188","display_name":"Invertible matrix","level":2,"score":0.29179999232292175},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.28529998660087585},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.2782999873161316},{"id":"https://openalex.org/C2780813799","wikidata":"https://www.wikidata.org/wiki/Q3274237","display_name":"Zero (linguistics)","level":2,"score":0.273499995470047},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.2703999876976013},{"id":"https://openalex.org/C2779803651","wikidata":"https://www.wikidata.org/wiki/Q5282088","display_name":"Discriminator","level":3,"score":0.2703000009059906},{"id":"https://openalex.org/C8038995","wikidata":"https://www.wikidata.org/wiki/Q1152135","display_name":"Unsupervised learning","level":2,"score":0.2687000036239624},{"id":"https://openalex.org/C165838908","wikidata":"https://www.wikidata.org/wiki/Q736777","display_name":"Calibration","level":2,"score":0.25619998574256897},{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.2524000108242035}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:doi:10.48550/arxiv.2602.11364","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"publisher-specific-oa","license_id":"https://openalex.org/licenses/publisher-specific-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},{"id":"doi:10.48550/arxiv.2602.11364","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2602.11364","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":"pmh:doi:10.48550/arxiv.2602.11364","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"publisher-specific-oa","license_id":"https://openalex.org/licenses/publisher-specific-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},"sustainable_development_goals":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.6619052290916443}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Large":[0],"Language":[1],"Models":[2],"(LLMs)":[3],"frequently":[4],"hallucinate":[5],"plausible":[6],"but":[7],"incorrect":[8],"assertions,":[9],"a":[10,45,66,75,105,122],"vulnerability":[11],"often":[12],"missed":[13],"by":[14,133,157],"uncertainty":[15],"metrics":[16],"when":[17],"models":[18],"are":[19,50,59],"confidently":[20],"wrong.":[21],"We":[22,52,71,102],"propose":[23,104],"DiffuTruth,":[24],"an":[25,89],"unsupervised":[26,127],"framework":[27],"that":[28,37],"reconceptualizes":[29],"fact":[30],"verification":[31],"via":[32],"non":[33],"equilibrium":[34],"thermodynamics,":[35],"positing":[36],"factual":[38,100],"truths":[39],"act":[40],"as":[41],"stable":[42],"attractors":[43],"on":[44,117,149],"generative":[46],"manifold":[47],"while":[48],"hallucinations":[49],"unstable.":[51],"introduce":[53],"the":[54,78,82,125,137,150,162],"Generative":[55],"Stress":[56],"Test,":[57],"claims":[58],"corrupted":[60],"with":[61,112],"noise":[62],"and":[63,85],"reconstructed":[64],"using":[65,88],"discrete":[67],"text":[68],"diffusion":[69],"model.":[70],"define":[72],"Semantic":[73,96],"Energy,":[74],"metric":[76],"measuring":[77],"semantic":[79],"divergence":[80],"between":[81],"original":[83],"claim":[84],"its":[86],"reconstruction":[87],"NLI":[90],"critic.":[91],"Unlike":[92],"vector":[93],"space":[94],"errors,":[95],"Energy":[97],"isolates":[98],"deep":[99],"contradictions.":[101],"further":[103],"Hybrid":[106],"Calibration":[107],"fusing":[108],"this":[109],"stability":[110],"signal":[111],"discriminative":[113],"confidence.":[114],"Extensive":[115],"experiments":[116],"FEVER":[118],"demonstrate":[119],"DiffuTruth":[120],"achieves":[121],"state":[123],"of":[124,129,139,164],"art":[126],"AUROC":[128],"0.725,":[130],"outperforming":[131,155],"baselines":[132,156],"1.5":[134],"percent":[135],"through":[136],"correction":[138],"overconfident":[140],"predictions.":[141],"Furthermore,":[142],"we":[143],"show":[144],"superior":[145],"zero":[146],"shot":[147],"generalization":[148],"multi":[151],"hop":[152],"HOVER":[153],"dataset,":[154],"over":[158],"4":[159],"percent,":[160],"confirming":[161],"robustness":[163],"thermodynamic":[165],"truth":[166],"properties":[167],"to":[168],"distribution":[169],"shifts.":[170]},"counts_by_year":[],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2026-02-14T00:00:00"}
