{"id":"https://openalex.org/W7160493609","doi":"https://doi.org/10.48550/arxiv.2605.04922","title":"Evolving Idea Graphs with Learnable Edits-and-Commits for Multi-Agent Scientific Ideation","display_name":"Evolving Idea Graphs with Learnable Edits-and-Commits for Multi-Agent Scientific Ideation","publication_year":2026,"publication_date":"2026-05-06","ids":{"openalex":"https://openalex.org/W7160493609","doi":"https://doi.org/10.48550/arxiv.2605.04922"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.04922","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.04922","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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.2605.04922","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5103055402","display_name":"Junfeng Dong","orcid":"https://orcid.org/0000-0003-2257-5983"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Dong, Jiangwen","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135573635","display_name":"Bo Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Bo","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5135550492","display_name":"Wanyu Lin","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lin, Wanyu","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/T11273","display_name":"Advanced Graph Neural Networks","score":0.5504000186920166,"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"}},"topics":[{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.5504000186920166,"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/T10028","display_name":"Topic Modeling","score":0.04580000042915344,"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/T13274","display_name":"Expert finding and Q&A systems","score":0.04270000010728836,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/commit","display_name":"Commit","score":0.6855000257492065},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5069000124931335},{"id":"https://openalex.org/keywords/encode","display_name":"ENCODE","score":0.49079999327659607},{"id":"https://openalex.org/keywords/strengths-and-weaknesses","display_name":"Strengths and weaknesses","score":0.4041000008583069},{"id":"https://openalex.org/keywords/ideation","display_name":"Ideation","score":0.3763999938964844},{"id":"https://openalex.org/keywords/directed-graph","display_name":"Directed graph","score":0.3716999888420105}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7365000247955322},{"id":"https://openalex.org/C153180980","wikidata":"https://www.wikidata.org/wiki/Q19776675","display_name":"Commit","level":2,"score":0.6855000257492065},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5069000124931335},{"id":"https://openalex.org/C66746571","wikidata":"https://www.wikidata.org/wiki/Q1134833","display_name":"ENCODE","level":3,"score":0.49079999327659607},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.4465000033378601},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4429999887943268},{"id":"https://openalex.org/C63882131","wikidata":"https://www.wikidata.org/wiki/Q17122954","display_name":"Strengths and weaknesses","level":2,"score":0.4041000008583069},{"id":"https://openalex.org/C170477896","wikidata":"https://www.wikidata.org/wiki/Q17039022","display_name":"Ideation","level":2,"score":0.3763999938964844},{"id":"https://openalex.org/C146380142","wikidata":"https://www.wikidata.org/wiki/Q1137726","display_name":"Directed graph","level":2,"score":0.3716999888420105},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.3416000008583069},{"id":"https://openalex.org/C62230096","wikidata":"https://www.wikidata.org/wiki/Q275969","display_name":"Crowdsourcing","level":2,"score":0.34049999713897705},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.3393999934196472},{"id":"https://openalex.org/C2988305597","wikidata":"https://www.wikidata.org/wiki/Q215772","display_name":"Evolving systems","level":2,"score":0.3264999985694885},{"id":"https://openalex.org/C2775924081","wikidata":"https://www.wikidata.org/wiki/Q55608371","display_name":"Control (management)","level":2,"score":0.28999999165534973},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.289000004529953},{"id":"https://openalex.org/C48103436","wikidata":"https://www.wikidata.org/wiki/Q599031","display_name":"State (computer science)","level":2,"score":0.28130000829696655},{"id":"https://openalex.org/C2984917352","wikidata":"https://www.wikidata.org/wiki/Q12772819","display_name":"Scientific discovery","level":2,"score":0.2720000147819519}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.04922","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.04922","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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.2605.04922","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.04922","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"LLM-empowered":[0],"multi-agent":[1,58],"systems":[2,168],"offer":[3],"new":[4],"potential":[5],"to":[6,33,111,129,140],"accelerate":[7],"scientific":[8,59,98],"discovery":[9],"by":[10],"generating":[11],"novel":[12],"research":[13,66],"ideas.":[14],"However,":[15],"existing":[16],"methods":[17],"typically":[18],"coordinate":[19],"agents":[20,44,139],"through":[21,82],"temporary":[22],"texts,":[23,83],"such":[24,72],"as":[25,73,90,153],"drafts":[26],"or":[27],"chat":[28],"logs;":[29],"it":[30],"is":[31,149],"difficult":[32],"pinpoint":[34],"the":[35,38,43,115,126,131,143,147,186],"weaknesses":[36,110],"in":[37],"generated":[39],"ideas":[40,67],"and":[41,76,100,106,162,174,190],"how":[42],"refine":[45],"them.":[46],"To":[47],"this":[48],"end,":[49],"we":[50],"introduce":[51],"\\textbf{Evolving":[52],"Idea":[53,159],"Graphs}":[54],"(EIG),":[55],"a":[56,86,120],"graph-based":[57],"ideation":[60],"framework":[61],"that":[62,181],"can":[63],"generate":[64],"high-performance":[65],"across":[68],"various":[69],"benchmark-native":[70],"metrics,":[71],"novelty,":[74],"feasibility,":[75],"clarity.":[77],"Instead":[78],"of":[79],"coordinating":[80],"solely":[81],"EIG":[84,164],"represents":[85],"partially":[87],"formed":[88],"proposal":[89,155],"an":[91],"evolving":[92,117,127],"idea":[93,116],"graph,":[94],"where":[95],"nodes":[96],"capture":[97],"claims":[99],"edges":[101],"encode":[102],"relations":[103],"(e.g.,":[104],"support":[105],"conflict),":[107],"enabling":[108],"unresolved":[109],"remain":[112],"identifiable":[113],"throughout":[114],"process.":[118],"Specifically,":[119],"learned":[121,191],"two-head":[122],"controller":[123],"operates":[124],"over":[125],"graph":[128,136,148,183],"guide":[130],"ideation:":[132],"one":[133],"head":[134],"selects":[135],"edits":[137],"for":[138,151],"execute,":[141],"while":[142],"other":[144],"decides":[145],"when":[146],"ready":[150],"commit":[152],"final":[154],"synthesis.":[156],"On":[157],"AI":[158],"Bench":[160],"2025":[161],"LiveIdeaBench,":[163],"outperforms":[165],"all":[166],"compared":[167],"on":[169],"both":[170],"automatic":[171],"benchmark":[172],"scores":[173],"blind":[175],"expert":[176],"ratings.":[177],"Ablations":[178],"further":[179],"show":[180],"explicit":[182],"state":[184],"provides":[185],"main":[187],"performance":[188],"gains,":[189],"edit-and-commit":[192],"control":[193],"adds":[194],"consistent":[195],"improvements.":[196]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-05-08T00:00:00"}
