{"id":"https://openalex.org/W7134229876","doi":"https://doi.org/10.48550/arxiv.2603.06366","title":"OralGPT-Plus: Learning to Use Visual Tools via Reinforcement Learning for Panoramic X-ray Analysis","display_name":"OralGPT-Plus: Learning to Use Visual Tools via Reinforcement Learning for Panoramic X-ray Analysis","publication_year":2026,"publication_date":"2026-03-06","ids":{"openalex":"https://openalex.org/W7134229876","doi":"https://doi.org/10.48550/arxiv.2603.06366"},"language":null,"primary_location":{"id":"pmh:doi:10.48550/arxiv.2603.06366","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},"type":"article","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/A5128467541","display_name":"Yuxuan Fan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Fan, Yuxuan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128605186","display_name":"Jing Hao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hao, Jing","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128436847","display_name":"Hong Chen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Hong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024403057","display_name":"Jiahao Bao","orcid":"https://orcid.org/0009-0001-1149-1410"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Bao, Jiahao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128603986","display_name":"Yihua Shao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shao, Yihua","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128507362","display_name":"Yuci Liang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liang, Yuci","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070510981","display_name":"Kuo Feng Hung","orcid":"https://orcid.org/0000-0002-3971-3484"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hung, Kuo Feng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5128431802","display_name":"Hao Tang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tang, Hao","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":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.24166464,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"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/T11363","display_name":"Dental Radiography and Imaging","score":0.30799999833106995,"subfield":{"id":"https://openalex.org/subfields/3504","display_name":"Oral Surgery"},"field":{"id":"https://openalex.org/fields/35","display_name":"Dentistry"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},"topics":[{"id":"https://openalex.org/T11363","display_name":"Dental Radiography and Imaging","score":0.30799999833106995,"subfield":{"id":"https://openalex.org/subfields/3504","display_name":"Oral Surgery"},"field":{"id":"https://openalex.org/fields/35","display_name":"Dentistry"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T11714","display_name":"Multimodal Machine Learning Applications","score":0.1428000032901764,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.07320000231266022,"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/panoramic-radiograph","display_name":"Panoramic radiograph","score":0.7427999973297119},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.6721000075340271},{"id":"https://openalex.org/keywords/construct","display_name":"Construct (python library)","score":0.5667999982833862},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.4560000002384186},{"id":"https://openalex.org/keywords/foundation","display_name":"Foundation (evidence)","score":0.38370001316070557},{"id":"https://openalex.org/keywords/medical-imaging","display_name":"Medical imaging","score":0.30979999899864197}],"concepts":[{"id":"https://openalex.org/C100548800","wikidata":"https://www.wikidata.org/wiki/Q743868","display_name":"Panoramic radiograph","level":3,"score":0.7427999973297119},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.6721000075340271},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.592199981212616},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5712000131607056},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.5667999982833862},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.4560000002384186},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4000999927520752},{"id":"https://openalex.org/C2780966255","wikidata":"https://www.wikidata.org/wiki/Q5474306","display_name":"Foundation (evidence)","level":2,"score":0.38370001316070557},{"id":"https://openalex.org/C31601959","wikidata":"https://www.wikidata.org/wiki/Q931309","display_name":"Medical imaging","level":2,"score":0.30979999899864197},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.30979999899864197},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.30720001459121704},{"id":"https://openalex.org/C67203356","wikidata":"https://www.wikidata.org/wiki/Q1321905","display_name":"Reinforcement","level":2,"score":0.28459998965263367},{"id":"https://openalex.org/C18762648","wikidata":"https://www.wikidata.org/wiki/Q42213","display_name":"Work (physics)","level":2,"score":0.2770000100135803},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.26649999618530273},{"id":"https://openalex.org/C534262118","wikidata":"https://www.wikidata.org/wiki/Q177719","display_name":"Medical diagnosis","level":2,"score":0.25529998540878296},{"id":"https://openalex.org/C2776291640","wikidata":"https://www.wikidata.org/wiki/Q2912517","display_name":"Value (mathematics)","level":2,"score":0.25459998846054077},{"id":"https://openalex.org/C2779982483","wikidata":"https://www.wikidata.org/wiki/Q6094420","display_name":"Iterative refinement","level":2,"score":0.2540999948978424}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:doi:10.48550/arxiv.2603.06366","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},{"id":"doi:10.48550/arxiv.2603.06366","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.06366","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":"pmh:doi:10.48550/arxiv.2603.06366","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","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":{"Panoramic":[0],"dental":[1,49,155],"radiographs":[2],"require":[3],"fine-grained":[4],"spatial":[5],"reasoning,":[6],"bilateral":[7],"symmetry":[8],"understanding,":[9],"and":[10,43,73,89,96,116,126,134,143,157],"multi-step":[11],"diagnostic":[12,45,64],"verification,":[13],"yet":[14],"existing":[15],"vision-language":[16,37],"models":[17],"operate":[18],"under":[19],"a":[20,59,79,159],"static":[21],"single-pass":[22],"paradigm":[23],"that":[24,66,84],"limits":[25],"their":[26],"clinical":[27],"reliability.":[28],"In":[29,100],"this":[30,54],"paper,":[31],"we":[32,56,102],"introduce":[33],"OralGPT-Plus,":[34],"an":[35],"agentic":[36,152],"model":[38],"designed":[39],"to":[40],"perform":[41],"iterative":[42],"symmetry-aware":[44],"reasoning":[46,92],"for":[47,70,108,154,161],"panoramic":[48,110,136,167],"radiograph":[50,168],"analysis.":[51,169],"To":[52],"support":[53],"paradigm,":[55],"construct":[57],"DentalProbe,":[58],"five-thousand-image":[60],"dataset":[61],"with":[62,93],"expert-curated":[63],"trajectories":[65],"provide":[67],"structured":[68],"supervision":[69],"localized":[71],"inspection":[72],"contralateral":[74],"comparison.":[75],"We":[76],"further":[77],"develop":[78],"Reinspection-driven":[80],"reinforcement":[81],"learning":[82],"framework":[83],"encourages":[85],"clinically":[86,165],"meaningful":[87],"re-examination":[88],"stabilizes":[90],"long-horizon":[91],"rubric-based":[94],"reward":[95],"conditioned":[97],"diagnostic-driven":[98],"reward.":[99],"parallel,":[101],"present":[103],"MMOral-X,":[104],"the":[105,139,149],"first":[106],"benchmark":[107],"holistic":[109],"diagnosis,":[111],"containing":[112],"300":[113],"open-ended":[114],"questions":[115],"region-level":[117],"annotations":[118],"across":[119],"multiple":[120],"difficulty":[121],"levels.":[122],"OralGPT-Plus":[123],"demonstrates":[124],"consistent":[125],"reliable":[127],"improvements":[128],"over":[129],"strong":[130],"baselines":[131],"on":[132],"MMOral-X":[133],"established":[135],"benchmarks,":[137],"indicating":[138],"effectiveness":[140],"of":[141,151],"interactive":[142],"symmetry-informed":[144],"reasoning.":[145],"Our":[146],"work":[147],"highlights":[148],"value":[150],"modeling":[153],"imaging":[156],"provides":[158],"foundation":[160],"future":[162],"research":[163],"in":[164],"aligned":[166]},"counts_by_year":[],"updated_date":"2026-07-15T18:14:33.161393","created_date":"2026-03-10T00:00:00"}