{"id":"https://openalex.org/W7152103030","doi":"https://doi.org/10.48550/arxiv.2604.05018","title":"PaperOrchestra: A Multi-Agent Framework for Automated AI Research Paper Writing","display_name":"PaperOrchestra: A Multi-Agent Framework for Automated AI Research Paper Writing","publication_year":2026,"publication_date":"2026-04-06","ids":{"openalex":"https://openalex.org/W7152103030","doi":"https://doi.org/10.48550/arxiv.2604.05018"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.05018","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.05018","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":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2604.05018","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5133160606","display_name":"Yiwen Song","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Song, Yiwen","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100566791","display_name":"Yale Song","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Song, Yale","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133199500","display_name":"Tomas Pfister","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Pfister, Tomas","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5133228254","display_name":"Jinsung Yoon","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yoon, Jinsung","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5133160606"],"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/T11948","display_name":"Machine Learning in Materials Science","score":0.33160001039505005,"subfield":{"id":"https://openalex.org/subfields/2505","display_name":"Materials Chemistry"},"field":{"id":"https://openalex.org/fields/25","display_name":"Materials Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11948","display_name":"Machine Learning in Materials Science","score":0.33160001039505005,"subfield":{"id":"https://openalex.org/subfields/2505","display_name":"Materials Chemistry"},"field":{"id":"https://openalex.org/fields/25","display_name":"Materials Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11986","display_name":"Scientific Computing and Data Management","score":0.08079999685287476,"subfield":{"id":"https://openalex.org/subfields/1802","display_name":"Information Systems and Management"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11714","display_name":"Multimodal Machine Learning Applications","score":0.07699999958276749,"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/suite","display_name":"Suite","score":0.8177000284194946},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.6546000242233276},{"id":"https://openalex.org/keywords/margin","display_name":"Margin (machine learning)","score":0.6435999870300293},{"id":"https://openalex.org/keywords/automation","display_name":"Automation","score":0.41110000014305115},{"id":"https://openalex.org/keywords/scientific-literature","display_name":"Scientific literature","score":0.2678999900817871}],"concepts":[{"id":"https://openalex.org/C79581498","wikidata":"https://www.wikidata.org/wiki/Q1367530","display_name":"Suite","level":2,"score":0.8177000284194946},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6887000203132629},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6546000242233276},{"id":"https://openalex.org/C774472","wikidata":"https://www.wikidata.org/wiki/Q6760393","display_name":"Margin (machine learning)","level":2,"score":0.6435999870300293},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4814000129699707},{"id":"https://openalex.org/C115901376","wikidata":"https://www.wikidata.org/wiki/Q184199","display_name":"Automation","level":2,"score":0.41110000014305115},{"id":"https://openalex.org/C115903868","wikidata":"https://www.wikidata.org/wiki/Q80993","display_name":"Software engineering","level":1,"score":0.4025000035762787},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.3384999930858612},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.28529998660087585},{"id":"https://openalex.org/C2781083858","wikidata":"https://www.wikidata.org/wiki/Q17327049","display_name":"Scientific literature","level":2,"score":0.2678999900817871},{"id":"https://openalex.org/C195344581","wikidata":"https://www.wikidata.org/wiki/Q2555318","display_name":"Automated reasoning","level":2,"score":0.262800008058548},{"id":"https://openalex.org/C2781020372","wikidata":"https://www.wikidata.org/wiki/Q533093","display_name":"On the fly","level":2,"score":0.2614000141620636},{"id":"https://openalex.org/C14224292","wikidata":"https://www.wikidata.org/wiki/Q13600188","display_name":"Conceptual framework","level":2,"score":0.2533000111579895},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.2508000135421753}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.05018","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.05018","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":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2604.05018","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.05018","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":"article"},"sustainable_development_goals":[{"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4","score":0.8708868026733398}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Synthesizing":[0],"unstructured":[1],"research":[2,40],"materials":[3,48,79],"into":[4,49],"manuscripts":[5],"is":[6],"an":[7,103],"essential":[8],"yet":[9],"under-explored":[10],"challenge":[11],"in":[12,110,116],"AI-driven":[13],"scientific":[14],"discovery.":[15],"Existing":[16],"autonomous":[17,100],"writers":[18],"are":[19],"rigidly":[20],"coupled":[21],"to":[22],"specific":[23],"experimental":[24],"pipelines,":[25],"and":[26,57,63,114],"produce":[27],"superficial":[28],"literature":[29,55,111],"reviews.":[30],"We":[31],"introduce":[32],"PaperOrchestra,":[33],"a":[34,87],"multi-agent":[35],"framework":[36],"for":[37],"automated":[38,91],"AI":[39,83],"paper":[41],"writing.":[42],"It":[43],"flexibly":[44],"transforms":[45],"unconstrained":[46],"pre-writing":[47],"submission-ready":[50],"LaTeX":[51],"manuscripts,":[52],"including":[53],"comprehensive":[54,88],"synthesis":[56],"generated":[58],"visuals,":[59],"such":[60],"as":[61],"plots":[62],"conceptual":[64],"diagrams.":[65],"To":[66],"evaluate":[67],"performance,":[68],"we":[69],"present":[70],"PaperWritingBench,":[71],"the":[72],"first":[73],"standardized":[74],"benchmark":[75],"of":[76,90,108],"reverse-engineered":[77],"raw":[78],"from":[80],"200":[81],"top-tier":[82],"conference":[84],"papers,":[85],"alongside":[86],"suite":[89],"evaluators.":[92],"In":[93],"side-by-side":[94],"human":[95],"evaluations,":[96],"PaperOrchestra":[97],"significantly":[98],"outperforms":[99],"baselines,":[101],"achieving":[102],"absolute":[104],"win":[105],"rate":[106],"margin":[107],"50%-68%":[109],"review":[112],"quality,":[113],"14%-38%":[115],"overall":[117],"manuscript":[118],"quality.":[119]},"counts_by_year":[],"updated_date":"2026-04-09T06:13:59.934233","created_date":"2026-04-09T00:00:00"}
