{"id":"https://openalex.org/W7155050158","doi":"https://doi.org/10.48550/arxiv.2604.16587","title":"Real-Time Visual Attribution Streaming in Thinking Model","display_name":"Real-Time Visual Attribution Streaming in Thinking Model","publication_year":2026,"publication_date":"2026-04-17","ids":{"openalex":"https://openalex.org/W7155050158","doi":"https://doi.org/10.48550/arxiv.2604.16587"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.16587","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.16587","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.2604.16587","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5134101610","display_name":"Seil Kang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kang, Seil","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134192356","display_name":"Woojung Han","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Han, Woojung","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134136723","display_name":"Junhyeok Kim","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kim, Junhyeok","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103029311","display_name":"Jin-Yeong Kim","orcid":"https://orcid.org/0000-0002-2432-5665"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kim, Jinyeong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134184854","display_name":"Youngeun Kim","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kim, Youngeun","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5022991142","display_name":"Seong Jae Hwang","orcid":"https://orcid.org/0000-0002-3713-5553"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hwang, Seong Jae","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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.7710999846458435,"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":0.7710999846458435,"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/T10799","display_name":"Data Visualization and Analytics","score":0.02879999950528145,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.02070000022649765,"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/attribution","display_name":"Attribution","score":0.7330999970436096},{"id":"https://openalex.org/keywords/visual-reasoning","display_name":"Visual reasoning","score":0.5002999901771545},{"id":"https://openalex.org/keywords/causal-model","display_name":"Causal model","score":0.4790000021457672},{"id":"https://openalex.org/keywords/causal-reasoning","display_name":"Causal reasoning","score":0.45210000872612},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.39739999175071716},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.3675000071525574},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.3208000063896179}],"concepts":[{"id":"https://openalex.org/C143299363","wikidata":"https://www.wikidata.org/wiki/Q900584","display_name":"Attribution","level":2,"score":0.7330999970436096},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6359000205993652},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5063999891281128},{"id":"https://openalex.org/C2777508537","wikidata":"https://www.wikidata.org/wiki/Q7936620","display_name":"Visual reasoning","level":2,"score":0.5002999901771545},{"id":"https://openalex.org/C11671645","wikidata":"https://www.wikidata.org/wiki/Q5054567","display_name":"Causal model","level":2,"score":0.4790000021457672},{"id":"https://openalex.org/C115086926","wikidata":"https://www.wikidata.org/wiki/Q17004651","display_name":"Causal reasoning","level":3,"score":0.45210000872612},{"id":"https://openalex.org/C180747234","wikidata":"https://www.wikidata.org/wiki/Q23373","display_name":"Cognitive psychology","level":1,"score":0.41839998960494995},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.39739999175071716},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.3799999952316284},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.3675000071525574},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.32589998841285706},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.3208000063896179},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.3111000061035156},{"id":"https://openalex.org/C66024118","wikidata":"https://www.wikidata.org/wiki/Q1122506","display_name":"Computational model","level":2,"score":0.30790001153945923},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.2953000068664551},{"id":"https://openalex.org/C188147891","wikidata":"https://www.wikidata.org/wiki/Q147638","display_name":"Cognitive science","level":1,"score":0.2915000021457672},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.2809000015258789},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.27570000290870667},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.2721000015735626},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2671000063419342},{"id":"https://openalex.org/C64357122","wikidata":"https://www.wikidata.org/wiki/Q1149766","display_name":"Causality (physics)","level":2,"score":0.2653000056743622},{"id":"https://openalex.org/C178253425","wikidata":"https://www.wikidata.org/wiki/Q162668","display_name":"Visual perception","level":3,"score":0.2637999951839447}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.16587","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.16587","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.2604.16587","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.16587","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":[{"score":0.8042610883712769,"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"We":[0],"present":[1],"an":[2,70],"amortized":[3,71],"framework":[4],"for":[5],"real-time":[6],"visual":[7,36,111],"attribution":[8,112,131],"streaming":[9],"in":[10,35,89,132],"multimodal":[11,133],"thinking":[12,98,134],"models.":[13],"When":[14],"these":[15],"models":[16,135],"generate":[17],"code":[18],"from":[19,26,84],"a":[20],"screenshot":[21],"or":[22,52],"solve":[23],"math":[24],"problems":[25],"images,":[27],"their":[28],"long":[29],"reasoning":[30],"traces":[31],"should":[32],"be":[33],"grounded":[34],"evidence.":[37],"However,":[38],"verifying":[39],"this":[40],"reliance":[41],"is":[42,136],"challenging:":[43],"faithful":[44,130],"causal":[45,63,78,107],"methods":[46,108],"require":[47],"costly":[48],"repeated":[49],"backward":[50],"passes":[51],"perturbations,":[53],"while":[54,109],"raw":[55],"attention":[56,90],"maps":[57],"offer":[58],"instant":[59],"access,":[60],"they":[61],"lack":[62],"validity.":[64],"To":[65],"resolve":[66],"this,":[67],"we":[68],"introduce":[69],"approach":[72,101],"that":[73,128],"learns":[74],"to":[75,105],"estimate":[76],"the":[77,85,120],"effects":[79],"of":[80],"semantic":[81],"regions":[82],"directly":[83],"rich":[86],"signals":[87],"encoded":[88],"features.":[91],"Across":[92],"five":[93],"diverse":[94],"benchmarks":[95],"and":[96],"four":[97],"models,":[99],"our":[100],"achieves":[102],"faithfulness":[103],"comparable":[104],"exhaustive":[106],"enabling":[110],"streaming,":[113],"where":[114],"users":[115],"observe":[116],"grounding":[117],"evidence":[118],"as":[119],"model":[121],"reasons,":[122],"not":[123,141],"after.":[124],"Our":[125],"results":[126],"demonstrate":[127],"real-time,":[129],"achievable":[137],"through":[138],"lightweight":[139],"learning,":[140],"brute-force":[142],"computation.":[143]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-04-22T00:00:00"}