{"id":"https://openalex.org/W7131290818","doi":"https://doi.org/10.48550/arxiv.2602.18731","title":"Beyond Description: A Multimodal Agent Framework for Insightful Chart Summarization","display_name":"Beyond Description: A Multimodal Agent Framework for Insightful Chart Summarization","publication_year":2026,"publication_date":"2026-02-21","ids":{"openalex":"https://openalex.org/W7131290818","doi":"https://doi.org/10.48550/arxiv.2602.18731"},"language":null,"primary_location":{"id":"pmh:doi:10.48550/arxiv.2602.18731","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"publisher-specific-oa","license_id":"https://openalex.org/licenses/publisher-specific-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":null,"any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5126718345","display_name":"Yuhang Bai","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Bai, Yuhang","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5126739574","display_name":"Yujuan Ding","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ding, Yujuan","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Lin, Shanru","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lin, Shanru","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":null,"display_name":"Fan, Wenqi","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Fan, Wenqi","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5126718345"],"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/T10601","display_name":"Handwritten Text Recognition Techniques","score":0.2603999972343445,"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/T10601","display_name":"Handwritten Text Recognition Techniques","score":0.2603999972343445,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.1923000067472458,"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":0.11110000312328339,"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/automatic-summarization","display_name":"Automatic summarization","score":0.9221000075340271},{"id":"https://openalex.org/keywords/chart","display_name":"Chart","score":0.6808000206947327},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.5792999863624573},{"id":"https://openalex.org/keywords/data-collection","display_name":"Data collection","score":0.3124000132083893},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.28110000491142273}],"concepts":[{"id":"https://openalex.org/C170858558","wikidata":"https://www.wikidata.org/wiki/Q1394144","display_name":"Automatic summarization","level":2,"score":0.9221000075340271},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8463000059127808},{"id":"https://openalex.org/C190812933","wikidata":"https://www.wikidata.org/wiki/Q28923","display_name":"Chart","level":2,"score":0.6808000206947327},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.5792999863624573},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4805000126361847},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.3589000105857849},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.35040000081062317},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.32749998569488525},{"id":"https://openalex.org/C133462117","wikidata":"https://www.wikidata.org/wiki/Q4929239","display_name":"Data collection","level":2,"score":0.3124000132083893},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.3100999891757965},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.28459998965263367},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.28110000491142273},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.263700008392334},{"id":"https://openalex.org/C2776187449","wikidata":"https://www.wikidata.org/wiki/Q1513879","display_name":"Natural language generation","level":3,"score":0.25850000977516174}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:doi:10.48550/arxiv.2602.18731","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"publisher-specific-oa","license_id":"https://openalex.org/licenses/publisher-specific-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},{"id":"doi:10.48550/arxiv.2602.18731","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2602.18731","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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"pmh:doi:10.48550/arxiv.2602.18731","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"publisher-specific-oa","license_id":"https://openalex.org/licenses/publisher-specific-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},"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":{"Chart":[0,53],"summarization":[1,125],"is":[2],"crucial":[3],"for":[4],"enhancing":[5],"data":[6,29,45,107],"accessibility":[7],"and":[8,31,65,131],"the":[9,36,41,63,81,118,123],"efficient":[10],"consumption":[11],"of":[12,44,68,83,96,120],"information.":[13],"However,":[14],"existing":[15],"methods,":[16],"including":[17],"those":[18],"with":[19,100,129],"Multimodal":[20],"Large":[21],"Language":[22],"Models":[23],"(MLLMs),":[24],"primarily":[25],"focus":[26],"on":[27,122],"low-level":[28],"descriptions":[30],"often":[32],"fail":[33],"to":[34,70,79],"capture":[35],"deeper":[37],"insights":[38,73],"which":[39],"are":[40],"fundamental":[42],"purpose":[43],"visualization.":[46],"To":[47],"address":[48],"this":[49],"challenge,":[50],"we":[51,86],"propose":[52],"Insight":[54],"Agent":[55],"Flow,":[56],"a":[57,89,93],"plan-and-execute":[58],"multi-agent":[59],"framework":[60],"effectively":[61],"leveraging":[62],"perceptual":[64],"reasoning":[66],"capabilities":[67],"MLLMs":[69,121],"uncover":[71],"profound":[72],"directly":[74],"from":[75],"chart":[76,124],"images.":[77],"Furthermore,":[78],"overcome":[80],"lack":[82],"suitable":[84],"benchmarks,":[85],"introduce":[87],"ChartSummInsights,":[88],"new":[90],"dataset":[91],"featuring":[92],"diverse":[94,132],"collection":[95],"real-world":[97],"charts":[98],"paired":[99],"high-quality,":[101],"insightful":[102],"summaries":[103,128],"authored":[104],"by":[105],"human":[106],"analysis":[108],"experts.":[109],"Experimental":[110],"results":[111],"demonstrate":[112],"that":[113],"our":[114],"method":[115],"significantly":[116],"improves":[117],"performance":[119],"task,":[126],"producing":[127],"deep":[130],"insights.":[133]},"counts_by_year":[],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2026-02-25T00:00:00"}