{"id":"https://openalex.org/W4416933474","doi":"https://doi.org/10.1109/iccv51701.2025.00047","title":"ChartPoint: Guiding MLLMs with Grounding Reflection for Chart Reasoning","display_name":"ChartPoint: Guiding MLLMs with Grounding Reflection for Chart Reasoning","publication_year":2025,"publication_date":"2025-10-19","ids":{"openalex":"https://openalex.org/W4416933474","doi":"https://doi.org/10.1109/iccv51701.2025.00047"},"language":null,"primary_location":{"id":"doi:10.1109/iccv51701.2025.00047","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccv51701.2025.00047","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE/CVF International Conference on Computer Vision (ICCV)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2512.00305","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101898915","display_name":"Zhengzhuo Xu","orcid":"https://orcid.org/0000-0003-4620-9187"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhengzhuo Xu","raw_affiliation_strings":["Tsinghua University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tsinghua University","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102598017","display_name":"Sinan Du","orcid":null},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"SiNan Du","raw_affiliation_strings":["Tsinghua University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tsinghua University","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5056609151","display_name":"Yiyan Qi","orcid":"https://orcid.org/0000-0002-8078-5834"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yiyan Qi","raw_affiliation_strings":["International Digital Economy Academy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"International Digital Economy Academy","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5120537496","display_name":"SiwenLu","orcid":null},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Siwen Lu","raw_affiliation_strings":["Beihang University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beihang University","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022319543","display_name":"Chengjin Xu","orcid":"https://orcid.org/0000-0002-4942-9049"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chengjin Xu","raw_affiliation_strings":["International Digital Economy Academy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"International Digital Economy Academy","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101456902","display_name":"Chun Yuan","orcid":"https://orcid.org/0000-0002-3590-6676"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chun Yuan","raw_affiliation_strings":["Tsinghua University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tsinghua University","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5051656423","display_name":"Jian Guo","orcid":"https://orcid.org/0000-0002-1123-4764"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jian Guo","raw_affiliation_strings":["International Digital Economy Academy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"International Digital Economy Academy","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"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":"426","last_page":"436"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10601","display_name":"Handwritten Text Recognition Techniques","score":0.4205999970436096,"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":0.4205999970436096,"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":0.05979999899864197,"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":0.05909999832510948,"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/visual-reasoning","display_name":"Visual reasoning","score":0.782800018787384},{"id":"https://openalex.org/keywords/chart","display_name":"Chart","score":0.7717000246047974},{"id":"https://openalex.org/keywords/bounding-overwatch","display_name":"Bounding overwatch","score":0.6412000060081482},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.6261000037193298},{"id":"https://openalex.org/keywords/reflection","display_name":"Reflection (computer programming)","score":0.6251999735832214},{"id":"https://openalex.org/keywords/construct","display_name":"Construct (python library)","score":0.49709999561309814},{"id":"https://openalex.org/keywords/bridge","display_name":"Bridge (graph theory)","score":0.4632999897003174}],"concepts":[{"id":"https://openalex.org/C2777508537","wikidata":"https://www.wikidata.org/wiki/Q7936620","display_name":"Visual reasoning","level":2,"score":0.782800018787384},{"id":"https://openalex.org/C190812933","wikidata":"https://www.wikidata.org/wiki/Q28923","display_name":"Chart","level":2,"score":0.7717000246047974},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.753000020980835},{"id":"https://openalex.org/C63584917","wikidata":"https://www.wikidata.org/wiki/Q333286","display_name":"Bounding overwatch","level":2,"score":0.6412000060081482},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.6261000037193298},{"id":"https://openalex.org/C65682993","wikidata":"https://www.wikidata.org/wiki/Q1056451","display_name":"Reflection (computer programming)","level":2,"score":0.6251999735832214},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5666999816894531},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.49709999561309814},{"id":"https://openalex.org/C100776233","wikidata":"https://www.wikidata.org/wiki/Q2532492","display_name":"Bridge (graph theory)","level":2,"score":0.4632999897003174},{"id":"https://openalex.org/C168993435","wikidata":"https://www.wikidata.org/wiki/Q6501125","display_name":"Ground","level":2,"score":0.4521999955177307},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.4316999912261963},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.4253999888896942},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.3714999854564667},{"id":"https://openalex.org/C99844830","wikidata":"https://www.wikidata.org/wiki/Q102441924","display_name":"Scaling","level":2,"score":0.33340001106262207},{"id":"https://openalex.org/C75553542","wikidata":"https://www.wikidata.org/wiki/Q178161","display_name":"A priori and a posteriori","level":2,"score":0.31029999256134033},{"id":"https://openalex.org/C147037132","wikidata":"https://www.wikidata.org/wiki/Q6865426","display_name":"Minimum bounding box","level":3,"score":0.2937999963760376},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.25699999928474426}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/iccv51701.2025.00047","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccv51701.2025.00047","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE/CVF International Conference on Computer Vision (ICCV)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2512.00305","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2512.00305","pdf_url":"https://arxiv.org/pdf/2512.00305","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2512.00305","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2512.00305","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":"pmh:oai:arXiv.org:2512.00305","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2512.00305","pdf_url":"https://arxiv.org/pdf/2512.00305","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G4213465990","display_name":null,"funder_award_id":"2022YFB4701400/4701402","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"}],"funders":[{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Multimodal":[0],"Large":[1],"Language":[2],"Models":[3],"(MLLMs)":[4],"have":[5],"emerged":[6],"as":[7,70],"powerful":[8],"tools":[9],"for":[10],"chart":[11,28,65,138,164],"comprehension.":[12],"However,":[13],"they":[14,40],"heavily":[15],"rely":[16],"on":[17,37,110,168],"extracted":[18],"content":[19],"via":[20],"OCR,":[21],"which":[22,90,159],"leads":[23],"to":[24,42,75,79,102,130],"numerical":[25],"hallucinations":[26],"when":[27],"textual":[29,117],"annotations":[30],"are":[31],"sparse.":[32],"While":[33],"existing":[34],"methods":[35],"focus":[36],"scaling":[38],"instructions,":[39],"fail":[41],"address":[43],"the":[44],"fundamental":[45],"challenge,":[46],"i.e.,":[47],"reasoning":[48,96,118],"with":[49,140],"visual":[50,121],"perception.":[51],"In":[52],"this":[53,85,149],"paper,":[54],"we":[55,87,113,151],"identify":[56],"a":[57,133],"critical":[58],"observation:":[59],"MLLMs":[60,101],"exhibit":[61],"weak":[62],"grounding":[63,122],"in":[64,97],"elements":[66],"and":[67,106,120,145,157],"proportional":[68],"relationships,":[69],"evidenced":[71],"by":[72],"their":[73,81],"inability":[74],"localize":[76],"key":[77],"positions":[78],"match":[80],"reasoning.":[82],"To":[83],"bridge":[84],"gap,":[86],"propose":[88],"PointCoT,":[89],"integrates":[91],"reflective":[92],"interaction":[93],"into":[94],"chain-of-thought":[95],"charts.":[98],"By":[99],"prompting":[100],"generate":[103],"bounding":[104,143],"boxes":[105],"re-render":[107],"charts":[108],"based":[109],"location":[111],"annotations,":[112],"establish":[114],"connections":[115],"between":[116],"steps":[119],"regions.":[123],"We":[124],"further":[125],"introduce":[126],"an":[127],"automated":[128],"pipeline":[129],"construct":[131],"ChartPoint-SFT-62k,":[132],"dataset":[134],"featuring":[135],"19.2K":[136],"high-quality":[137],"samples":[139],"step-by-step":[141],"CoT,":[142],"box,":[144],"re-rendered":[146],"visualizations.":[147],"Leveraging":[148],"data,":[150],"develop":[152],"two":[153],"instruction-tuned":[154],"models,":[155],"ChartPointQ2":[156],"ChartPointQ2.5,":[158],"outperform":[160],"state-of-the-art":[161],"across":[162],"several":[163],"benchmarks,":[165],"e.g.,":[166],"+5.04\\%":[167],"ChartBench.":[169]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2025-12-03T00:00:00"}