{"id":"https://openalex.org/W7165921758","doi":"https://doi.org/10.48550/arxiv.2606.25325","title":"Omni-Perception Policy Optimization for Multimodal Emotion Reasoning","display_name":"Omni-Perception Policy Optimization for Multimodal Emotion Reasoning","publication_year":2026,"publication_date":"2026-06-24","ids":{"openalex":"https://openalex.org/W7165921758","doi":"https://doi.org/10.48550/arxiv.2606.25325"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.25325","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.25325","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,"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.2606.25325","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5040690037","display_name":"Zhiyuan Han","orcid":"https://orcid.org/0000-0001-6421-8605"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Han, Zhiyuan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009738035","display_name":"Beier Zhu","orcid":"https://orcid.org/0000-0002-7900-6979"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhu, Beier","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139346854","display_name":"Wenwen Tong","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tong, Wenwen","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139308041","display_name":"Pengyang Shao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shao, Pengyang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015177224","display_name":"Peipei Song","orcid":"https://orcid.org/0000-0001-6764-3375"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Song, Peipei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139347420","display_name":"Xinyi Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Xinyi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139368669","display_name":"Jiangnan Chen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Jiangnan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139370799","display_name":"Lewei Lu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lu, Lewei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5030018760","display_name":"Xiaomin Yang","orcid":"https://orcid.org/0000-0002-5593-5108"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yang, Xun","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/T10667","display_name":"Emotion and Mood Recognition","score":0.6850000023841858,"subfield":{"id":"https://openalex.org/subfields/3205","display_name":"Experimental and Cognitive Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T10667","display_name":"Emotion and Mood Recognition","score":0.6850000023841858,"subfield":{"id":"https://openalex.org/subfields/3205","display_name":"Experimental and Cognitive Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11714","display_name":"Multimodal Machine Learning Applications","score":0.07580000162124634,"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/T10462","display_name":"Reinforcement Learning in Robotics","score":0.02630000002682209,"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/hallucinating","display_name":"Hallucinating","score":0.8611000180244446},{"id":"https://openalex.org/keywords/perception","display_name":"Perception","score":0.5900999903678894},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.4715000092983246},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.46709999442100525},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.35420000553131104},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.2750000059604645}],"concepts":[{"id":"https://openalex.org/C2911011789","wikidata":"https://www.wikidata.org/wiki/Q130741","display_name":"Hallucinating","level":2,"score":0.8611000180244446},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6503000259399414},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.5900999903678894},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5626000165939331},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.4715000092983246},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.46709999442100525},{"id":"https://openalex.org/C180747234","wikidata":"https://www.wikidata.org/wiki/Q23373","display_name":"Cognitive psychology","level":1,"score":0.41990000009536743},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.35420000553131104},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3138999938964844},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.2750000059604645},{"id":"https://openalex.org/C2780910867","wikidata":"https://www.wikidata.org/wiki/Q1952416","display_name":"Multimodality","level":2,"score":0.2718999981880188},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.26190000772476196},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.25760000944137573}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.25325","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.25325","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,"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.2606.25325","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.25325","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,"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":[{"display_name":"Peace, Justice and strong institutions","score":0.5752836465835571,"id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"We":[0,99],"find":[1],"that":[2,46,68,106,113],"current":[3],"emotion-oriented":[4],"Omni-MLLMs":[5],"still":[6],"lack":[7],"reliable":[8],"omni-modal":[9],"perception:":[10],"they":[11],"(i)":[12],"underutilize":[13],"multimodal":[14,49,141],"cues":[15,64],"in":[16],"their":[17],"reasoning":[18,57],"trajectories":[19,67],"and":[20,62,65,82,109,120,126,136],"(ii)":[21],"exhibit":[22],"unfaithful":[23],"behavior,":[24],"often":[25],"hallucinating":[26],"modality-specific":[27,92],"statements":[28],"from":[29],"other":[30],"modalities.":[31],"Building":[32],"on":[33,118,129],"these":[34,71],"insights,":[35],"we":[36],"propose":[37],"OPPO":[38,114],"(Omni-Perception":[39],"Policy":[40],"Optimization),":[41],"a":[42,87,103],"reinforcement":[43],"learning":[44],"framework":[45],"explicitly":[47],"optimizes":[48],"perception.":[50],"First,":[51],"an":[52,74],"Omni-Perception":[53,75],"Reward":[54],"decomposes":[55],"ground-truth":[56],"into":[58],"fine-grained":[59],"visual,":[60],"acoustic,":[61],"emotion":[63,142],"rewards":[66],"semantically":[69],"recover":[70],"cues.":[72],"Second,":[73],"Loss":[76],"compares":[77],"the":[78,132],"policy":[79],"under":[80],"full":[81],"unimodally":[83],"masked":[84],"inputs,":[85],"applying":[86],"KL":[88],"penalty":[89],"only":[90],"to":[91,95],"evidence":[93],"tokens":[94],"suppress":[96],"cross-modal":[97],"hallucination.":[98],"further":[100],"introduce":[101],"MEP-Bench,":[102,130],"diagnostic":[104],"benchmark":[105],"quantifies":[107],"utilization":[108,125],"faithfulness.":[110],"Experiments":[111],"show":[112],"achieves":[115],"state-of-the-art":[116],"performance":[117],"MER-UniBench":[119],"MME-Emotion,":[121],"while":[122],"substantially":[123],"improving":[124],"faithfulness":[127],"scores":[128],"highlighting":[131],"importance":[133],"of":[134],"sufficient":[135],"faithful":[137],"omni":[138],"perception":[139],"for":[140],"reasoning.":[143]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-06-26T00:00:00"}