{"id":"https://openalex.org/W7161692795","doi":"https://doi.org/10.48550/arxiv.2605.16409","title":"Multilingual OCR-Aware Fine-Tuning and Prompt-Guided Chain-of-Thought Reasoning for Multimodal Large Language Models","display_name":"Multilingual OCR-Aware Fine-Tuning and Prompt-Guided Chain-of-Thought Reasoning for Multimodal Large Language Models","publication_year":2026,"publication_date":"2026-05-13","ids":{"openalex":"https://openalex.org/W7161692795","doi":"https://doi.org/10.48550/arxiv.2605.16409"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.16409","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.16409","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":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.2605.16409","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5136498045","display_name":"Qinwu Xu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xu, Qinwu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136467909","display_name":"Yifan Jiang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jiang, Yifan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5058712662","display_name":"Ren H","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ren, Haoyu","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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.5437999963760376,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.5437999963760376,"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/T10601","display_name":"Handwritten Text Recognition Techniques","score":0.3912999927997589,"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/T10028","display_name":"Topic Modeling","score":0.019099999219179153,"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/robustness","display_name":"Robustness (evolution)","score":0.6434999704360962},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.4334999918937683},{"id":"https://openalex.org/keywords/prior-probability","display_name":"Prior probability","score":0.40470001101493835},{"id":"https://openalex.org/keywords/machine-translation","display_name":"Machine translation","score":0.4034999907016754},{"id":"https://openalex.org/keywords/language-model","display_name":"Language model","score":0.39809998869895935},{"id":"https://openalex.org/keywords/visualization","display_name":"Visualization","score":0.34700000286102295},{"id":"https://openalex.org/keywords/translation","display_name":"Translation (biology)","score":0.337799996137619},{"id":"https://openalex.org/keywords/optical-character-recognition","display_name":"Optical character recognition","score":0.33500000834465027}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7825999855995178},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6633999943733215},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6434999704360962},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.6000999808311462},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.4334999918937683},{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.40470001101493835},{"id":"https://openalex.org/C203005215","wikidata":"https://www.wikidata.org/wiki/Q79798","display_name":"Machine translation","level":2,"score":0.4034999907016754},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.39809998869895935},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.38600000739097595},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.34700000286102295},{"id":"https://openalex.org/C149364088","wikidata":"https://www.wikidata.org/wiki/Q185917","display_name":"Translation (biology)","level":4,"score":0.337799996137619},{"id":"https://openalex.org/C546480517","wikidata":"https://www.wikidata.org/wiki/Q167555","display_name":"Optical character recognition","level":3,"score":0.33500000834465027},{"id":"https://openalex.org/C174348530","wikidata":"https://www.wikidata.org/wiki/Q188635","display_name":"Bridging (networking)","level":2,"score":0.2987000048160553},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.2980000078678131},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.29100000858306885},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.28839999437332153},{"id":"https://openalex.org/C2983448237","wikidata":"https://www.wikidata.org/wiki/Q1078276","display_name":"Language understanding","level":2,"score":0.28110000491142273},{"id":"https://openalex.org/C23224414","wikidata":"https://www.wikidata.org/wiki/Q176769","display_name":"Hidden Markov model","level":2,"score":0.27149999141693115},{"id":"https://openalex.org/C135641252","wikidata":"https://www.wikidata.org/wiki/Q738567","display_name":"Multimodal interaction","level":2,"score":0.2630999982357025},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.25920000672340393}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.16409","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.16409","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":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2605.16409","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.16409","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":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education","score":0.6918215751647949}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Optical":[0],"character":[1],"recognition":[2],"(OCR)":[3],"and":[4,29,56,84,100,127,149,157,162,179,186],"multilingual":[5,36,81,93,184],"text":[6,130],"understanding":[7],"remain":[8],"major":[9],"failure":[10],"modes":[11],"of":[12,122],"multimodal":[13,37,72,145,174],"large":[14],"language":[15,135],"models":[16],"(MLLMs),":[17],"particularly":[18],"in":[19],"real-world":[20],"images":[21,102],"containing":[22],"cluttered":[23],"layouts,":[24],"small":[25],"fonts,":[26],"blur,":[27],"occlusion,":[28],"complex":[30],"typography.":[31],"We":[32],"present":[33],"an":[34,177],"OCR-aware":[35,49,117,173],"training":[38],"framework":[39,76,119],"that":[40,171],"combines":[41],"(i)":[42],"large-scale":[43],"synthetic":[44],"OCR-to-translation":[45],"data":[46],"generation,":[47],"(ii)":[48],"supervised":[50],"fine-tuning":[51],"(SFT)":[52],"with":[53,109,143],"LoRA":[54],"adaptation,":[55],"(iii)":[57],"structured":[58],"visual":[59,67,88,188],"chain-of-thought":[60],"(CoT)":[61],"prompting":[62],"for":[63,182],"reasoning":[64],"under":[65,86,137,160],"uncertain":[66,138],"conditions.":[68,89,140],"Using":[69],"a":[70],"LLaMA-based":[71],"architecture,":[73],"the":[74,110,115,168],"proposed":[75,116],"substantially":[77],"improves":[78,120],"OCR":[79,139,155,165,185],"completeness,":[80],"translation":[82],"accuracy,":[83],"robustness":[85],"degraded":[87],"Experimental":[90],"results":[91,169],"on":[92,134],"receipts,":[94],"menus,":[95],"posters,":[96],"signs,":[97],"handwritten":[98],"text,":[99],"document":[101],"demonstrate":[103],"significantly":[104],"improved":[105,154],"visual-text":[106],"grounding":[107,156],"compared":[108],"baseline":[111],"model.":[112],"In":[113],"particular,":[114],"post-training":[118,175],"extraction":[121],"small,":[123],"blurred,":[124],"spatially":[125],"scattered,":[126],"partially":[128],"occluded":[129],"while":[131],"reducing":[132],"reliance":[133],"priors":[136],"Qualitative":[141],"comparisons":[142],"frontier":[144],"systems,":[146],"including":[147],"GPT-5-class":[148],"Gemini-family":[150],"models,":[151],"further":[152],"suggest":[153],"reduced":[158],"hallucination":[159],"noisy":[161],"visually":[163],"ambiguous":[164],"scenarios.":[166],"Overall,":[167],"indicate":[170],"data-centric":[172],"provides":[176],"effective":[178],"scalable":[180],"direction":[181],"improving":[183],"OCR-based":[187],"question":[189],"answering":[190],"systems.":[191]},"counts_by_year":[],"updated_date":"2026-07-23T08:03:31.855105","created_date":"2026-05-20T00:00:00"}