{"id":"https://openalex.org/W7140893054","doi":"https://doi.org/10.48550/arxiv.2603.24326","title":"Boosting Document Parsing Efficiency and Performance with Coarse-to-Fine Visual Processing","display_name":"Boosting Document Parsing Efficiency and Performance with Coarse-to-Fine Visual Processing","publication_year":2026,"publication_date":"2026-03-25","ids":{"openalex":"https://openalex.org/W7140893054","doi":"https://doi.org/10.48550/arxiv.2603.24326"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.24326","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.24326","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":"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.2603.24326","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5130686489","display_name":"Cheng Cui","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Cui, Cheng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130663975","display_name":"Ting Sun","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sun, Ting","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130645560","display_name":"Suyin Liang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liang, Suyin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015786581","display_name":"Tingquan Gao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gao, Tingquan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130689523","display_name":"Zelun Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Zelun","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130656293","display_name":"Jiaxuan Liu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Jiaxuan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130702302","display_name":"Xueqing Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Xueqing","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043005394","display_name":"Changda Zhou","orcid":"https://orcid.org/0000-0003-1597-8522"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhou, Changda","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130690190","display_name":"Hongen Liu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Hongen","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076353846","display_name":"Manhui Lin","orcid":"https://orcid.org/0000-0002-6933-9788"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lin, Manhui","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130662234","display_name":"Yue H. Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Yue","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130639851","display_name":"Yubo Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Yubo","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130711930","display_name":"Jing Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Jing","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130682022","display_name":"Jun Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Jun","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130645547","display_name":"Xing Wei","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wei, Xing","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130704476","display_name":"Yi Liu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Yi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5084155236","display_name":"Dianhai Yu","orcid":"https://orcid.org/0000-0002-0163-2603"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yu, Dianhai","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5130636584","display_name":"Yanjun Ma","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ma, Yanjun","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/T10601","display_name":"Handwritten Text Recognition Techniques","score":0.5019999742507935,"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":0.5019999742507935,"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/T10181","display_name":"Natural Language Processing Techniques","score":0.08330000191926956,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.04129999876022339,"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/parsing","display_name":"Parsing","score":0.7441999912261963},{"id":"https://openalex.org/keywords/boosting","display_name":"Boosting (machine learning)","score":0.7192000150680542},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.6039000153541565},{"id":"https://openalex.org/keywords/redundancy","display_name":"Redundancy (engineering)","score":0.49000000953674316},{"id":"https://openalex.org/keywords/inefficiency","display_name":"Inefficiency","score":0.41760000586509705},{"id":"https://openalex.org/keywords/source-code","display_name":"Source code","score":0.33079999685287476},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.3179999887943268}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8410000205039978},{"id":"https://openalex.org/C186644900","wikidata":"https://www.wikidata.org/wiki/Q194152","display_name":"Parsing","level":2,"score":0.7441999912261963},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.7192000150680542},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.6039000153541565},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5353000164031982},{"id":"https://openalex.org/C152124472","wikidata":"https://www.wikidata.org/wiki/Q1204361","display_name":"Redundancy (engineering)","level":2,"score":0.49000000953674316},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.45829999446868896},{"id":"https://openalex.org/C2778869765","wikidata":"https://www.wikidata.org/wiki/Q6028363","display_name":"Inefficiency","level":2,"score":0.41760000586509705},{"id":"https://openalex.org/C43126263","wikidata":"https://www.wikidata.org/wiki/Q128751","display_name":"Source code","level":2,"score":0.33079999685287476},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.3179999887943268},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.2912999987602234},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.2903999984264374},{"id":"https://openalex.org/C157657479","wikidata":"https://www.wikidata.org/wiki/Q2367247","display_name":"Closed captioning","level":3,"score":0.28439998626708984},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.2818000018596649},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.27959999442100525},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.25699999928474426},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.2540999948978424}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.24326","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.24326","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":"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.2603.24326","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.24326","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":"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":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Document":[0],"parsing":[1,148,181],"is":[2],"a":[3,30,64,87,112],"fine-grained":[4],"task":[5],"where":[6],"image":[7],"resolution":[8],"significantly":[9,40,153],"impacts":[10],"performance.":[11,83],"While":[12],"advanced":[13],"research":[14],"leveraging":[15],"vision-language":[16,117],"models":[17,192],"benefits":[18],"from":[19],"high-resolution":[20],"input":[21],"to":[22,29,48,102,120,128],"boost":[23],"model":[24,118],"performance,":[25],"this":[26,46],"often":[27],"leads":[28],"quadratic":[31],"increase":[32],"in":[33,53,145],"the":[34,133,176],"number":[35],"of":[36,132,178],"vision":[37,105,171],"tokens":[38,172],"and":[39,82,97,110,149,163,173,184,191],"raises":[41],"computational":[42],"costs.":[43],"We":[44],"attribute":[45],"inefficiency":[47],"substantial":[49],"visual":[50],"regions":[51,73],"redundancy":[52],"document":[54,186],"images,":[55],"like":[56],"background.":[57],"To":[58],"tackle":[59],"this,":[60],"we":[61,85,108],"propose":[62],"PaddleOCR-VL,":[63],"novel":[65],"coarse-to-fine":[66,180],"architecture":[67],"that":[68,140],"focuses":[69],"on":[70],"semantically":[71],"relevant":[72],"while":[74,167],"suppressing":[75],"redundant":[76],"ones,":[77],"thereby":[78],"improving":[79],"both":[80,146],"efficiency":[81],"Specifically,":[84],"introduce":[86],"lightweight":[88],"Valid":[89],"Region":[90],"Focus":[91],"Module":[92],"(VRFM)":[93],"which":[94],"leverages":[95],"localization":[96],"contextual":[98],"relationship":[99],"prediction":[100],"capabilities":[101],"identify":[103],"valid":[104],"tokens.":[106],"Subsequently,":[107],"design":[109],"train":[111],"compact":[113],"yet":[114],"powerful":[115],"0.9B":[116],"(PaddleOCR-VL-0.9B)":[119],"perform":[121],"detailed":[122],"recognition,":[123],"guided":[124],"by":[125],"VRFM":[126],"outputs":[127],"avoid":[129],"direct":[130],"processing":[131],"entire":[134],"large":[135],"image.":[136],"Extensive":[137],"experiments":[138],"demonstrate":[139],"PaddleOCR-VL":[141],"achieves":[142],"state-of-the-art":[143],"performance":[144],"page-level":[147],"element-level":[150],"recognition.":[151],"It":[152],"outperforms":[154],"existing":[155],"solutions,":[156],"exhibits":[157],"strong":[158],"competitiveness":[159],"against":[160],"top-tier":[161],"VLMs,":[162],"delivers":[164],"fast":[165],"inference":[166],"utilizing":[168],"substantially":[169],"fewer":[170],"parameters,":[174],"highlighting":[175],"effectiveness":[177],"targeted":[179],"for":[182],"accurate":[183],"efficient":[185],"understanding.":[187],"The":[188],"source":[189],"code":[190],"are":[193],"publicly":[194],"available":[195],"at":[196],"https://github.com/PaddlePaddle/PaddleOCR.":[197]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-03-27T00:00:00"}
