{"id":"https://openalex.org/W7162756919","doi":"https://doi.org/10.48550/arxiv.2605.29861","title":"Towards Verifiable Multimodal Deep Research: A Multi-Agent Harness for Interleaved Report Generation","display_name":"Towards Verifiable Multimodal Deep Research: A Multi-Agent Harness for Interleaved Report Generation","publication_year":2026,"publication_date":"2026-05-28","ids":{"openalex":"https://openalex.org/W7162756919","doi":"https://doi.org/10.48550/arxiv.2605.29861"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.29861","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.29861","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.2605.29861","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5137381014","display_name":"Chenghao Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Chenghao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137348181","display_name":"Guanting Dong","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Dong, Guanting","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137385003","display_name":"Yufan Liu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Yufan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137390767","display_name":"Tong Zhao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhao, Tong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137367546","display_name":"Zhicheng Dou","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Xiaoxi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":null,"display_name":"Dou, Zhicheng","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Dou, Zhicheng","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":0.7572000026702881,"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":0.7572000026702881,"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":0.1257999986410141,"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":0.015200000256299973,"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/verifiable-secret-sharing","display_name":"Verifiable secret sharing","score":0.798799991607666},{"id":"https://openalex.org/keywords/usable","display_name":"USable","score":0.704800009727478},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.6507999897003174},{"id":"https://openalex.org/keywords/protocol","display_name":"Protocol (science)","score":0.5831000208854675},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4999000132083893},{"id":"https://openalex.org/keywords/construct","display_name":"Construct (python library)","score":0.4943999946117401},{"id":"https://openalex.org/keywords/visualization","display_name":"Visualization","score":0.32010000944137573}],"concepts":[{"id":"https://openalex.org/C85847156","wikidata":"https://www.wikidata.org/wiki/Q59015987","display_name":"Verifiable secret sharing","level":3,"score":0.798799991607666},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7961000204086304},{"id":"https://openalex.org/C2780615836","wikidata":"https://www.wikidata.org/wiki/Q2471869","display_name":"USable","level":2,"score":0.704800009727478},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.6507999897003174},{"id":"https://openalex.org/C2780385302","wikidata":"https://www.wikidata.org/wiki/Q367158","display_name":"Protocol (science)","level":3,"score":0.5831000208854675},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5016000270843506},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4999000132083893},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.4943999946117401},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.3813000023365021},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.32010000944137573},{"id":"https://openalex.org/C111498074","wikidata":"https://www.wikidata.org/wiki/Q173326","display_name":"Formal verification","level":2,"score":0.31189998984336853},{"id":"https://openalex.org/C170130773","wikidata":"https://www.wikidata.org/wiki/Q216378","display_name":"Usability","level":2,"score":0.3052000105381012},{"id":"https://openalex.org/C44291984","wikidata":"https://www.wikidata.org/wiki/Q1074173","display_name":"Question answering","level":2,"score":0.3046000003814697},{"id":"https://openalex.org/C115903868","wikidata":"https://www.wikidata.org/wiki/Q80993","display_name":"Software engineering","level":1,"score":0.3019999861717224},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.29100000858306885},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.28209999203681946},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.27810001373291016},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.2623000144958496},{"id":"https://openalex.org/C110251889","wikidata":"https://www.wikidata.org/wiki/Q1569697","display_name":"Model checking","level":2,"score":0.2574999928474426},{"id":"https://openalex.org/C2777877512","wikidata":"https://www.wikidata.org/wiki/Q1116097","display_name":"Common ground","level":2,"score":0.2524999976158142}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.29861","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.29861","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.2605.29861","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.29861","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":[{"score":0.4533565044403076,"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Large":[0],"Language":[1],"Models":[2],"(LLMs)":[3],"have":[4],"advanced":[5],"autonomous":[6],"agents":[7,80],"from":[8,65],"deep":[9,17,29,141],"search,":[10],"which":[11,19],"retrieves":[12],"concise":[13],"factual":[14,113],"answers,":[15],"to":[16,34,44,68],"research,":[18,74],"synthesizes":[20],"scattered":[21],"evidence":[22],"into":[23],"long-form":[24],"reports.":[25],"However,":[26],"verifiable":[27],"multimodal":[28,100,155],"research":[30,142],"remains":[31],"challenging":[32],"due":[33],"open-ended":[35],"synthesis":[36],"without":[37],"deterministic":[38],"ground":[39],"truth":[40],"and":[41,75,95,117,136,152],"the":[42,63,108,121],"need":[43],"interleave":[45],"textual":[46],"arguments":[47],"with":[48,134],"visual":[49],"evidence.":[50],"We":[51,123],"propose":[52],"Ptah,":[53],"a":[54,91],"multi-agent":[55],"harness":[56],"for":[57],"interleaved":[58],"report":[59,71],"generation.":[60],"Ptah":[61,146],"orchestrates":[62],"lifecycle":[64],"user":[66],"query":[67],"rendered":[69],"web":[70],"through":[72,98],"planning,":[73],"writing":[76],"stages,":[77],"where":[78],"specialized":[79],"construct":[81],"visual-aware":[82],"plans,":[83],"collect":[84],"claim-grounded":[85],"evidence,":[86],"maintain":[87],"source-aligned":[88],"images":[89],"in":[90],"Visual":[92],"Working":[93],"Memory,":[94],"compose":[96],"reports":[97,156],"declarative":[99],"tool":[101],"use.":[102],"A":[103],"verifier":[104],"agent":[105],"serves":[106],"as":[107],"harness's":[109],"acceptance":[110],"function,":[111],"enforcing":[112],"grounding,":[114],"citation":[115],"fidelity,":[116],"cross-modal":[118],"consistency":[119],"throughout":[120],"workflow.":[122],"further":[124],"introduce":[125],"PtahEval,":[126],"an":[127],"evaluation":[128],"protocol":[129],"that":[130,145],"augments":[131],"existing":[132],"benchmarks":[133,143],"image-level":[135],"presentation-level":[137],"assessments.":[138],"Experiments":[139],"on":[140],"show":[144],"produces":[147],"more":[148],"reliable,":[149],"visually":[150],"informative,":[151],"usable":[153],"human-facing":[154],"than":[157],"strong":[158],"baselines.":[159],"Our":[160],"code":[161],"is":[162],"released":[163],"at":[164],"https://github.com/SnowNation101/Ptah":[165]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-05-30T00:00:00"}
