{"id":"https://openalex.org/W7160952126","doi":"https://doi.org/10.48550/arxiv.2605.08847","title":"EmoS: A High-Fidelity Multimodal Benchmark for Fine-grained Streaming Emotional Understanding","display_name":"EmoS: A High-Fidelity Multimodal Benchmark for Fine-grained Streaming Emotional Understanding","publication_year":2026,"publication_date":"2026-05-09","ids":{"openalex":"https://openalex.org/W7160952126","doi":"https://doi.org/10.48550/arxiv.2605.08847"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.08847","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.08847","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":null,"license_id":null,"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.2605.08847","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5135968808","display_name":"Pengze Guo","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Guo, Pengze","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135969792","display_name":"Jingxi Liang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liang, Jingxi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101705596","display_name":"Zhiwen Xie","orcid":"https://orcid.org/0000-0003-0837-3285"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xie, Zhiwen","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101633505","display_name":"Qifeng Wang","orcid":"https://orcid.org/0000-0001-8544-9007"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Qifeng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5120001875","display_name":"Derek F. Wong","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wong, Derek F.","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":0.6960999965667725,"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":0.6960999965667725,"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/T12488","display_name":"Mental Health via Writing","score":0.1071000024676323,"subfield":{"id":"https://openalex.org/subfields/3207","display_name":"Social 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/T13702","display_name":"Machine Learning in Healthcare","score":0.0357000008225441,"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/benchmark","display_name":"Benchmark (surveying)","score":0.7791000008583069},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5759000182151794},{"id":"https://openalex.org/keywords/ground-truth","display_name":"Ground truth","score":0.5364000201225281},{"id":"https://openalex.org/keywords/empirical-research","display_name":"Empirical research","score":0.4864000082015991},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.4832000136375427},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.45969998836517334},{"id":"https://openalex.org/keywords/empathy","display_name":"Empathy","score":0.4431999921798706},{"id":"https://openalex.org/keywords/annotation","display_name":"Annotation","score":0.350600004196167}],"concepts":[{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.7791000008583069},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7613999843597412},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5759000182151794},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.5364000201225281},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5304999947547913},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4975000023841858},{"id":"https://openalex.org/C120936955","wikidata":"https://www.wikidata.org/wiki/Q2155640","display_name":"Empirical research","level":2,"score":0.4864000082015991},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.4832000136375427},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.45969998836517334},{"id":"https://openalex.org/C2779885105","wikidata":"https://www.wikidata.org/wiki/Q182263","display_name":"Empathy","level":2,"score":0.4431999921798706},{"id":"https://openalex.org/C2776321320","wikidata":"https://www.wikidata.org/wiki/Q857525","display_name":"Annotation","level":2,"score":0.350600004196167},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.3456999957561493},{"id":"https://openalex.org/C2780966255","wikidata":"https://www.wikidata.org/wiki/Q5474306","display_name":"Foundation (evidence)","level":2,"score":0.3456000089645386},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.32749998569488525},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.3073999881744385},{"id":"https://openalex.org/C62989814","wikidata":"https://www.wikidata.org/wiki/Q854648","display_name":"Gossip","level":2,"score":0.29660001397132874},{"id":"https://openalex.org/C121687571","wikidata":"https://www.wikidata.org/wiki/Q4677630","display_name":"Activity recognition","level":2,"score":0.2928999960422516},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2921000123023987},{"id":"https://openalex.org/C2777438025","wikidata":"https://www.wikidata.org/wiki/Q1339090","display_name":"Emotion recognition","level":2,"score":0.29170000553131104},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.27959999442100525},{"id":"https://openalex.org/C30539005","wikidata":"https://www.wikidata.org/wiki/Q1066689","display_name":"Human communication","level":2,"score":0.26930001378059387},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.2678999900817871},{"id":"https://openalex.org/C59656382","wikidata":"https://www.wikidata.org/wiki/Q191536","display_name":"Conjunction (astronomy)","level":2,"score":0.25619998574256897}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.08847","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.08847","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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2605.08847","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.08847","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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"In":[0],"the":[1,8,49,108,111],"context":[2],"of":[3,15,51,115],"today's":[4],"high-pressure,":[5],"aging":[6],"society,":[7],"demand":[9],"for":[10,110],"large-scale":[11],"emotional":[12,87],"models":[13,119],"capable":[14],"providing":[16],"empathetic":[17],"support":[18],"is":[19],"more":[20],"critical":[21],"than":[22],"ever.":[23],"However,":[24],"existing":[25,57],"benchmarks":[26],"fail":[27],"to":[28,47],"simultaneously":[29],"achieve":[30],"ecological":[31,52],"validity,":[32],"signal":[33],"clarity,":[34],"and":[35,54,113,120,125],"reliable":[36],"fine-grained":[37],"labeling.":[38],"We":[39],"introduce":[40],"EmoS,":[41],"a":[42,66,73],"high-fidelity":[43],"bilingual":[44],"benchmark":[45],"designed":[46],"resolve":[48],"limitations":[50],"validity":[53],"noise":[55],"in":[56],"datasets":[58],"by":[59,72],"combining":[60],"strictly":[61],"filtered":[62],"static":[63],"slices":[64],"with":[65],"dynamic":[67],"Streaming":[68],"Monologue":[69],"subset.":[70],"Supported":[71],"rigorous":[74],"dual-layer":[75],"human":[76],"annotation":[77],"pipeline,":[78],"EmoS":[79,100],"provides":[80],"trusted":[81],"ground":[82],"truth":[83],"that":[84,92],"captures":[85],"continuous":[86],"evolution.":[88],"Empirical":[89],"results":[90],"show":[91],"fine-tuning":[93],"MLLMs":[94],"(multimodal":[95],"large":[96],"language":[97],"models)":[98],"on":[99],"yields":[101],"significant":[102],"gains":[103],"over":[104],"zero-shot":[105],"baselines,":[106],"laying":[107],"foundation":[109],"training":[112],"evaluation":[114],"future":[116],"emotion":[117],"recognition":[118],"empathy":[121],"models.":[122],"The":[123],"dataset":[124],"code":[126],"are":[127],"publicly":[128],"available":[129],"at":[130],"https://github.com/NLP2CT/EmoS.":[131]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-05-13T00:00:00"}
