{"id":"https://openalex.org/W7164852836","doi":"https://doi.org/10.1145/3805622.3810621","title":"Context Relation-Aware and Fine-Grained Token Interaction for Dialogue-Level Aspect-Based Sentiment Quadruple Analysis","display_name":"Context Relation-Aware and Fine-Grained Token Interaction for Dialogue-Level Aspect-Based Sentiment Quadruple Analysis","publication_year":2026,"publication_date":"2026-06-15","ids":{"openalex":"https://openalex.org/W7164852836","doi":"https://doi.org/10.1145/3805622.3810621"},"language":null,"primary_location":{"id":"doi:10.1145/3805622.3810621","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3805622.3810621","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2026 International Conference on Multimedia Retrieval","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1145/3805622.3810621","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5069411901","display_name":"J Jay Liu","orcid":"https://orcid.org/0000-0002-1166-2777"},"institutions":[{"id":"https://openalex.org/I152269853","display_name":"Qilu University of Technology","ror":"https://ror.org/04hyzq608","country_code":"CN","type":"education","lineage":["https://openalex.org/I152269853"]},{"id":"https://openalex.org/I4210142748","display_name":"Shandong Academy of Sciences","ror":"https://ror.org/04y8d6y55","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210142748"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiahui Liu","raw_affiliation_strings":["Qilu University of Technology (Shandong Academy of Sciences), Jinan, China"],"raw_orcid":"https://orcid.org/0009-0005-3730-6518","affiliations":[{"raw_affiliation_string":"Qilu University of Technology (Shandong Academy of Sciences), Jinan, China","institution_ids":["https://openalex.org/I152269853","https://openalex.org/I4210142748"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073081338","display_name":"Tao Sun","orcid":"https://orcid.org/0000-0003-2220-930X"},"institutions":[{"id":"https://openalex.org/I152269853","display_name":"Qilu University of Technology","ror":"https://ror.org/04hyzq608","country_code":"CN","type":"education","lineage":["https://openalex.org/I152269853"]},{"id":"https://openalex.org/I4210142748","display_name":"Shandong Academy of Sciences","ror":"https://ror.org/04y8d6y55","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210142748"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tao Sun","raw_affiliation_strings":["Qilu University of Technology (Shandong Academy of Sciences), Jinan, China"],"raw_orcid":"https://orcid.org/0000-0003-2220-930X","affiliations":[{"raw_affiliation_string":"Qilu University of Technology (Shandong Academy of Sciences), Jinan, China","institution_ids":["https://openalex.org/I152269853","https://openalex.org/I4210142748"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5113306185","display_name":"Zimeng Xu","orcid":"https://orcid.org/0009-0004-9189-8748"},"institutions":[{"id":"https://openalex.org/I152269853","display_name":"Qilu University of Technology","ror":"https://ror.org/04hyzq608","country_code":"CN","type":"education","lineage":["https://openalex.org/I152269853"]},{"id":"https://openalex.org/I4210142748","display_name":"Shandong Academy of Sciences","ror":"https://ror.org/04y8d6y55","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210142748"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zimeng Xu","raw_affiliation_strings":["Qilu University of Technology (Shandong Academy of Sciences), Jinan, China"],"raw_orcid":"https://orcid.org/0009-0004-9189-8748","affiliations":[{"raw_affiliation_string":"Qilu University of Technology (Shandong Academy of Sciences), Jinan, China","institution_ids":["https://openalex.org/I152269853","https://openalex.org/I4210142748"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103005683","display_name":"Zhipeng Shen","orcid":null},"institutions":[{"id":"https://openalex.org/I152269853","display_name":"Qilu University of Technology","ror":"https://ror.org/04hyzq608","country_code":"CN","type":"education","lineage":["https://openalex.org/I152269853"]},{"id":"https://openalex.org/I4210142748","display_name":"Shandong Academy of Sciences","ror":"https://ror.org/04y8d6y55","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210142748"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhipeng Shen","raw_affiliation_strings":["Qilu University of Technology (Shandong Academy of Sciences), Jinan, China"],"raw_orcid":"https://orcid.org/0009-0006-5161-4215","affiliations":[{"raw_affiliation_string":"Qilu University of Technology (Shandong Academy of Sciences), Jinan, China","institution_ids":["https://openalex.org/I152269853","https://openalex.org/I4210142748"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138679473","display_name":"Yifan Kong","orcid":"https://orcid.org/0009-0000-3819-3416"},"institutions":[{"id":"https://openalex.org/I152269853","display_name":"Qilu University of Technology","ror":"https://ror.org/04hyzq608","country_code":"CN","type":"education","lineage":["https://openalex.org/I152269853"]},{"id":"https://openalex.org/I4210142748","display_name":"Shandong Academy of Sciences","ror":"https://ror.org/04y8d6y55","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210142748"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yifan Kong","raw_affiliation_strings":["Qilu University of Technology (Shandong Academy of Sciences), Jinan, China"],"raw_orcid":"https://orcid.org/0009-0000-3819-3416","affiliations":[{"raw_affiliation_string":"Qilu University of Technology (Shandong Academy of Sciences), Jinan, China","institution_ids":["https://openalex.org/I152269853","https://openalex.org/I4210142748"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5078325795","display_name":"Jiaao Zhou","orcid":null},"institutions":[{"id":"https://openalex.org/I152269853","display_name":"Qilu University of Technology","ror":"https://ror.org/04hyzq608","country_code":"CN","type":"education","lineage":["https://openalex.org/I152269853"]},{"id":"https://openalex.org/I4210142748","display_name":"Shandong Academy of Sciences","ror":"https://ror.org/04y8d6y55","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210142748"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiaao Zhou","raw_affiliation_strings":["Qilu University of Technology (Shandong Academy of Sciences), Jinan, China"],"raw_orcid":"https://orcid.org/0009-0003-0014-117X","affiliations":[{"raw_affiliation_string":"Qilu University of Technology (Shandong Academy of Sciences), Jinan, China","institution_ids":["https://openalex.org/I152269853","https://openalex.org/I4210142748"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.95033543,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1851","last_page":"1860"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.47040000557899475,"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/T10028","display_name":"Topic Modeling","score":0.47040000557899475,"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/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.34310001134872437,"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/T10667","display_name":"Emotion and Mood Recognition","score":0.023399999365210533,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/security-token","display_name":"Security token","score":0.8113999962806702},{"id":"https://openalex.org/keywords/utterance","display_name":"Utterance","score":0.7178999781608582},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5644000172615051},{"id":"https://openalex.org/keywords/dependency","display_name":"Dependency (UML)","score":0.5396000146865845},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.531000018119812},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.5303999781608582},{"id":"https://openalex.org/keywords/sentiment-analysis","display_name":"Sentiment analysis","score":0.492000013589859},{"id":"https://openalex.org/keywords/dependency-graph","display_name":"Dependency graph","score":0.4336000084877014},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.4129999876022339}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8228999972343445},{"id":"https://openalex.org/C48145219","wikidata":"https://www.wikidata.org/wiki/Q1335365","display_name":"Security token","level":2,"score":0.8113999962806702},{"id":"https://openalex.org/C2775852435","wikidata":"https://www.wikidata.org/wiki/Q258403","display_name":"Utterance","level":2,"score":0.7178999781608582},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5644000172615051},{"id":"https://openalex.org/C19768560","wikidata":"https://www.wikidata.org/wiki/Q320727","display_name":"Dependency (UML)","level":2,"score":0.5396000146865845},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.531000018119812},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.5303999781608582},{"id":"https://openalex.org/C66402592","wikidata":"https://www.wikidata.org/wiki/Q2271421","display_name":"Sentiment analysis","level":2,"score":0.492000013589859},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4918000102043152},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.4544999897480011},{"id":"https://openalex.org/C16311509","wikidata":"https://www.wikidata.org/wiki/Q4148050","display_name":"Dependency graph","level":3,"score":0.4336000084877014},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.4129999876022339},{"id":"https://openalex.org/C4679612","wikidata":"https://www.wikidata.org/wiki/Q866298","display_name":"Aggregate (composite)","level":2,"score":0.3716999888420105},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.35199999809265137},{"id":"https://openalex.org/C38764148","wikidata":"https://www.wikidata.org/wiki/Q17098245","display_name":"Interaction information","level":2,"score":0.34119999408721924},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.3411000072956085},{"id":"https://openalex.org/C2164484","wikidata":"https://www.wikidata.org/wiki/Q5170150","display_name":"Core (optical fiber)","level":2,"score":0.33869999647140503},{"id":"https://openalex.org/C89611455","wikidata":"https://www.wikidata.org/wiki/Q6804646","display_name":"Mechanism (biology)","level":2,"score":0.336899995803833},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.33309999108314514},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.32170000672340393},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.3089999854564667},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.30410000681877136},{"id":"https://openalex.org/C195807954","wikidata":"https://www.wikidata.org/wiki/Q1662562","display_name":"Information extraction","level":2,"score":0.2721000015735626},{"id":"https://openalex.org/C183322885","wikidata":"https://www.wikidata.org/wiki/Q17007702","display_name":"Context model","level":3,"score":0.26579999923706055},{"id":"https://openalex.org/C206588197","wikidata":"https://www.wikidata.org/wiki/Q846574","display_name":"Reuse","level":2,"score":0.2635999917984009},{"id":"https://openalex.org/C106301342","wikidata":"https://www.wikidata.org/wiki/Q4117933","display_name":"Entropy (arrow of time)","level":2,"score":0.25949999690055847},{"id":"https://openalex.org/C96711827","wikidata":"https://www.wikidata.org/wiki/Q17012245","display_name":"Entity linking","level":3,"score":0.25780001282691956},{"id":"https://openalex.org/C2780762811","wikidata":"https://www.wikidata.org/wiki/Q1784941","display_name":"Cosine similarity","level":3,"score":0.2533000111579895},{"id":"https://openalex.org/C198942812","wikidata":"https://www.wikidata.org/wiki/Q496618","display_name":"Semantic property","level":2,"score":0.2531000077724457},{"id":"https://openalex.org/C2775945657","wikidata":"https://www.wikidata.org/wiki/Q381442","display_name":"Structuring","level":2,"score":0.25189998745918274}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3805622.3810621","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3805622.3810621","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2026 International Conference on Multimedia Retrieval","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3805622.3810621","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3805622.3810621","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2026 International Conference on Multimedia Retrieval","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":31,"referenced_works":["https://openalex.org/W2252024663","https://openalex.org/W2789190634","https://openalex.org/W2963264961","https://openalex.org/W2963341956","https://openalex.org/W2974004142","https://openalex.org/W2998446468","https://openalex.org/W3034884160","https://openalex.org/W3035537500","https://openalex.org/W3095340127","https://openalex.org/W3101602207","https://openalex.org/W3138389337","https://openalex.org/W3165080648","https://openalex.org/W3174994995","https://openalex.org/W3175404808","https://openalex.org/W3176138405","https://openalex.org/W3176920001","https://openalex.org/W4221146921","https://openalex.org/W4287854530","https://openalex.org/W4296366985","https://openalex.org/W4312908198","https://openalex.org/W4382202817","https://openalex.org/W4387425964","https://openalex.org/W4387426388","https://openalex.org/W4387427055","https://openalex.org/W4392904536","https://openalex.org/W4393147172","https://openalex.org/W4396723257","https://openalex.org/W4402670515","https://openalex.org/W4411485033","https://openalex.org/W4413966915","https://openalex.org/W4414009582"],"related_works":[],"abstract_inverted_index":{"Dialogue":[0],"Aspect-based":[1],"Sentiment":[2],"Quadruple":[3],"Analysis":[4],"(DiaASQ)":[5],"aims":[6],"to":[7,49,71,126,166],"extract":[8],"fine-grained":[9,55],"sentiment":[10,207],"quadruples":[11],"from":[12,19],"dialogues.":[13],"The":[14,92],"core":[15],"challenge":[16],"primarily":[17],"arises":[18],"the":[20,34,42,63,107,137,148,175,197,205],"fact":[21],"that":[22,81],"elements":[23],"within":[24],"a":[25,78,102,117,122,163],"quadruple":[26,208],"are":[27],"often":[28],"scattered":[29],"across":[30,184],"different":[31],"utterances,":[32],"necessitating":[33],"precise":[35],"modeling":[36],"of":[37,65,109,139,190],"cross-utterance":[38,169],"correlations":[39,99],"at":[40],"both":[41],"utterance":[43,98,140],"and":[44,54,87,121,131,172,192],"token":[45],"levels.Existing":[46],"approaches":[47],"struggle":[48],"effectively":[50],"capture":[51],"long-range":[52,111],"dependencies":[53],"semantic":[56,170],"interactions":[57],"in":[58,62,147,194,204],"dialogue":[59,72,104,149,206],"understanding,":[60],"resulting":[61],"loss":[64],"critical":[66],"information":[67,130,173],"while":[68],"being":[69],"susceptible":[70],"structure":[73],"biases.Therefore,":[74],"this":[75],"paper":[76],"proposes":[77],"novel":[79],"method":[80],"integrates":[82],"Relation-Aware":[83],"Context":[84],"Encoding":[85],"(RACE)":[86],"Fine-Grained":[88],"Token":[89],"Interaction":[90],"(FGTI).":[91],"RACE":[93],"module":[94,143],"explicitly":[95],"models":[96],"multi-hop":[97],"by":[100],"constructing":[101],"path-enhanced":[103],"graph,":[105],"alleviating":[106],"issue":[108],"insufficient":[110],"dependency":[112],"modeling.":[113],"It":[114,160,187],"further":[115,161],"leverages":[116],"graph":[118,150],"attention":[119],"network":[120],"token-level":[123,168],"filtering":[124],"mechanism":[125,165],"dynamically":[127],"aggregate":[128],"contextual":[129],"filter":[132],"key":[133],"content,":[134],"thereby":[135],"enhancing":[136],"quality":[138],"representations.The":[141],"FGTI":[142],"filters":[144],"redundant":[145],"edges":[146],"based":[151],"on":[152],"cosine":[153],"similarity,":[154],"retaining":[155],"only":[156],"highly":[157],"relevant":[158],"connections.":[159],"employs":[162],"cross-attention":[164],"achieve":[167],"alignment":[171],"complementarity.On":[174],"multilingual":[176],"DiaASQ":[177],"dataset,":[178],"our":[179],"model":[180],"outperforms":[181],"baseline":[182],"methods":[183],"all":[185],"metrics.":[186],"achieves":[188],"improvements":[189],"2.36%":[191],"1.11%":[193],"Iden-F1":[195],"over":[196],"best":[198],"baseline,":[199],"respectively,":[200],"demonstrating":[201],"its":[202],"effectiveness":[203],"extraction":[209],"task.":[210]},"counts_by_year":[],"updated_date":"2026-06-16T07:37:23.134862","created_date":"2026-06-16T00:00:00"}
