{"id":"https://openalex.org/W7151381547","doi":"https://doi.org/10.48550/arxiv.2604.03556","title":"Focus Matters: Phase-Aware Suppression for Hallucination in Vision-Language Models","display_name":"Focus Matters: Phase-Aware Suppression for Hallucination in Vision-Language Models","publication_year":2026,"publication_date":"2026-04-04","ids":{"openalex":"https://openalex.org/W7151381547","doi":"https://doi.org/10.48550/arxiv.2604.03556"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.03556","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.03556","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":"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"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2604.03556","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5133097278","display_name":"Sohyeon Kim","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kim, Sohyeon","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5063040463","display_name":"Sang Yeon Yoon","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yoon, Sang Yeon","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5000238164","display_name":"Kyeongbo Kong","orcid":"https://orcid.org/0000-0002-1135-7502"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kong, Kyeongbo","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"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":0.7304999828338623,"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":0.7304999828338623,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.041999999433755875,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.02669999934732914,"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/focus","display_name":"Focus (optics)","score":0.7756999731063843},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.7200000286102295},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.5544000267982483},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.5063999891281128},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.4821999967098236},{"id":"https://openalex.org/keywords/visual-hallucination","display_name":"Visual Hallucination","score":0.4438999891281128},{"id":"https://openalex.org/keywords/decoding-methods","display_name":"Decoding methods","score":0.4422000050544739},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.4253999888896942},{"id":"https://openalex.org/keywords/point-process","display_name":"Point process","score":0.3817000091075897}],"concepts":[{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.7756999731063843},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.7200000286102295},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.65829998254776},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6218000054359436},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.5544000267982483},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.5063999891281128},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.4821999967098236},{"id":"https://openalex.org/C2908998935","wikidata":"https://www.wikidata.org/wiki/Q130741","display_name":"Visual Hallucination","level":2,"score":0.4438999891281128},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.4422000050544739},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.4253999888896942},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4020000100135803},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.38589999079704285},{"id":"https://openalex.org/C88871306","wikidata":"https://www.wikidata.org/wiki/Q7208287","display_name":"Point process","level":2,"score":0.3817000091075897},{"id":"https://openalex.org/C12713177","wikidata":"https://www.wikidata.org/wiki/Q1900281","display_name":"Perspective (graphical)","level":2,"score":0.3653999865055084},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.30979999899864197},{"id":"https://openalex.org/C111370547","wikidata":"https://www.wikidata.org/wiki/Q7451120","display_name":"Sensory cue","level":2,"score":0.29670000076293945},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.29649999737739563},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.28540000319480896},{"id":"https://openalex.org/C157657479","wikidata":"https://www.wikidata.org/wiki/Q2367247","display_name":"Closed captioning","level":3,"score":0.27250000834465027},{"id":"https://openalex.org/C178253425","wikidata":"https://www.wikidata.org/wiki/Q162668","display_name":"Visual perception","level":3,"score":0.2689000070095062},{"id":"https://openalex.org/C64876066","wikidata":"https://www.wikidata.org/wiki/Q5141226","display_name":"Cognitive neuroscience of visual object recognition","level":3,"score":0.26339998841285706},{"id":"https://openalex.org/C180747234","wikidata":"https://www.wikidata.org/wiki/Q23373","display_name":"Cognitive psychology","level":1,"score":0.2619999945163727},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.26080000400543213},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.25920000672340393},{"id":"https://openalex.org/C106430172","wikidata":"https://www.wikidata.org/wiki/Q6002272","display_name":"Image restoration","level":4,"score":0.25850000977516174},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.2563000023365021},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.2522999942302704}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.03556","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.03556","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2604.03556","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.03556","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":"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"},"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":{"Large":[0],"Vision-Language":[1],"Models":[2],"(LVLMs)":[3],"have":[4],"achieved":[5],"impressive":[6],"progress":[7],"in":[8,26,41,55,71,127],"multimodal":[9],"reasoning,":[10],"yet":[11],"they":[12],"remain":[13],"prone":[14],"to":[15,33,96,145,179],"object":[16],"hallucinations,":[17],"generating":[18],"descriptions":[19],"of":[20,68,79],"objects":[21],"that":[22,90,115,164],"are":[23],"not":[24],"present":[25],"the":[27,42,64,102,121,165],"input":[28],"image.":[29],"Recent":[30],"approaches":[31],"attempt":[32],"mitigate":[34],"hallucinations":[35],"by":[36,106],"suppressing":[37],"unreliable":[38],"visual":[39,80,148],"signals":[40],"vision":[43,69],"encoder,":[44],"but":[45],"many":[46],"rely":[47],"on":[48],"iterative":[49],"optimization":[50],"for":[51],"each":[52],"input,":[53],"resulting":[54],"substantial":[56],"inference":[57,193],"latency.":[58,194],"In":[59],"this":[60,107],"work,":[61],"we":[62,109],"investigate":[63],"internal":[65],"attention":[66,100],"dynamics":[67],"encoders":[70],"LVLMs":[72],"and":[73,85,138,160],"identify":[74],"a":[75,111,128,134,140],"consistent":[76],"three-phase":[77],"structure":[78],"information":[81],"processing:":[82],"diffusion,":[83],"focus,":[84],"rediffusion.":[86],"Our":[87],"analysis":[88],"reveals":[89],"hallucination":[91,170,188],"behavior":[92],"is":[93],"particularly":[94],"sensitive":[95],"tokens":[97,119],"receiving":[98],"low":[99],"during":[101,120],"focus":[103,122],"phase.":[104,123],"Motivated":[105],"observation,":[108],"propose":[110],"lightweight":[112],"inference-time":[113],"intervention":[114],"selectively":[116],"suppresses":[117],"such":[118],"The":[124],"method":[125],"operates":[126],"training-free":[129],"manner":[130],"using":[131],"statistics":[132],"from":[133],"single":[135],"forward":[136],"pass":[137],"employs":[139],"Determinantal":[141],"Point":[142],"Process":[143],"(DPP)":[144],"preserve":[146],"diverse":[147],"cues":[149],"while":[150,172],"filtering":[151],"redundant":[152],"tokens.":[153],"Extensive":[154],"experiments":[155],"across":[156],"multiple":[157],"LVLM":[158],"backbones":[159],"decoding":[161],"strategies":[162],"demonstrate":[163],"proposed":[166],"approach":[167,185],"consistently":[168],"reduces":[169],"metrics":[171],"maintaining":[173],"competitive":[174],"caption":[175],"quality.":[176],"Moreover,":[177],"compared":[178],"adversarial":[180],"uncertainty":[181],"estimation":[182],"methods,":[183],"our":[184],"achieves":[186],"comparable":[187],"mitigation":[189],"with":[190],"negligible":[191],"additional":[192]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-04-08T00:00:00"}
