{"id":"https://openalex.org/W7168419542","doi":"https://doi.org/10.48550/arxiv.2607.12252","title":"FinResearchBench II: A Deep Research Benchmark with Consensus-Derived Gold Rubrics for Distinguishing Financial Report Quality","display_name":"FinResearchBench II: A Deep Research Benchmark with Consensus-Derived Gold Rubrics for Distinguishing Financial Report Quality","publication_year":2026,"publication_date":"2026-07-14","ids":{"openalex":"https://openalex.org/W7168419542","doi":"https://doi.org/10.48550/arxiv.2607.12252"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2607.12252","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2607.12252","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.2607.12252","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5140912009","display_name":"Beidi Luan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Luan, Beidi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5140801952","display_name":"Rui Sun","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sun, Rui","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5140782752","display_name":"Sinuo Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Sinuo","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5140935714","display_name":"Yan Gu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gu, Yan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5140920061","display_name":"Chao Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Chao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5140944940","display_name":"Zhenliang Xiong","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xiong, Zhenliang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5140926843","display_name":"Jing Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Jing","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5140774229","display_name":"Zuo Bai","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Bai, Zuo","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/T10081","display_name":"Auditing, Earnings Management, Governance","score":0.27070000767707825,"subfield":{"id":"https://openalex.org/subfields/1402","display_name":"Accounting"},"field":{"id":"https://openalex.org/fields/14","display_name":"Business, Management and Accounting"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T10081","display_name":"Auditing, Earnings Management, Governance","score":0.27070000767707825,"subfield":{"id":"https://openalex.org/subfields/1402","display_name":"Accounting"},"field":{"id":"https://openalex.org/fields/14","display_name":"Business, Management and Accounting"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T13794","display_name":"Financial Reporting and XBRL","score":0.21469999849796295,"subfield":{"id":"https://openalex.org/subfields/1404","display_name":"Management Information Systems"},"field":{"id":"https://openalex.org/fields/14","display_name":"Business, Management and Accounting"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11995","display_name":"FinTech, Crowdfunding, Digital Finance","score":0.09470000118017197,"subfield":{"id":"https://openalex.org/subfields/1404","display_name":"Management Information Systems"},"field":{"id":"https://openalex.org/fields/14","display_name":"Business, Management and Accounting"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/rubric","display_name":"Rubric","score":0.9861999750137329},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.7208999991416931},{"id":"https://openalex.org/keywords/pipeline","display_name":"Pipeline (software)","score":0.5978000164031982},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.5824000239372253},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.546999990940094},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.508400022983551}],"concepts":[{"id":"https://openalex.org/C111640148","wikidata":"https://www.wikidata.org/wiki/Q847349","display_name":"Rubric","level":2,"score":0.9861999750137329},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.7208999991416931},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.676800012588501},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.5978000164031982},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.5824000239372253},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.546999990940094},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.508400022983551},{"id":"https://openalex.org/C117251300","wikidata":"https://www.wikidata.org/wiki/Q1849855","display_name":"Parametric statistics","level":2,"score":0.42899999022483826},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.415800005197525},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.3937000036239624},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.38510000705718994},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3698999881744385},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.28769999742507935},{"id":"https://openalex.org/C184898388","wikidata":"https://www.wikidata.org/wiki/Q1435712","display_name":"Pairwise comparison","level":2,"score":0.2856999933719635},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.28540000319480896},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.2680000066757202}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2607.12252","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2607.12252","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.2607.12252","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2607.12252","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":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Deep":[0],"research":[1,53,214],"agents":[2],"are":[3],"increasingly":[4],"used":[5],"to":[6,22,108,223],"produce":[7],"long-form":[8],"financial":[9,51],"reports,":[10],"yet":[11],"large-scale":[12,112],"evaluation":[13,101,107],"remains":[14],"bottlenecked":[15],"by":[16,32],"the":[17,45,142,152,178,194,228],"need":[18],"for":[19,37,111,242],"human":[20,42,73,84,106],"experts":[21,43,74,85],"define":[23],"and":[24,60,97,155,171,192,236,248],"execute":[25],"high-quality":[26,39],"rubrics.":[27,200],"We":[28,48,123],"address":[29],"this":[30,202],"problem":[31],"proposing":[33],"a":[34,50,89,94,132,138,156,161],"scalable":[35,241],"pipeline":[36,229],"generating":[38],"rubrics":[40,66,128],"without":[41],"in":[44],"final":[46,195,203],"loop.":[47],"build":[49],"deep":[52,213],"benchmark":[54,243],"from":[55,67,75,82,88,221,233],"104":[56],"real-world":[57],"user":[58],"queries":[59],"automatically":[61],"synthesize":[62],"14,450":[63],"query-specific":[64],"candidate":[65],"model-generated":[68],"reports.":[69],"To":[70],"justify":[71],"removing":[72],"rubric":[76,80,113,139,162,204,234],"execution,":[77],"we":[78,206],"compare":[79],"judgments":[81],"three":[83,143],"with":[86,105,216],"those":[87],"three-LLM":[90],"judge":[91],"panel":[92],"on":[93,119,148],"sampled":[95],"subset,":[96],"show":[98],"that":[99],"LLM-based":[100],"is":[102,239],"sufficiently":[103],"consistent":[104],"replace":[109],"it":[110,165,238],"screening,":[114],"including":[115],"98.67\\%":[116],"label-level":[117],"agreement":[118],"jointly":[120],"unanimous":[121],"items.":[122],"then":[124],"derive":[125],"consensus-derived":[126,198],"gold":[127,199],"through":[129],"two":[130],"filters:":[131],"strict":[133],"consistency":[134],"filter,":[135,158],"which":[136,159,188],"keeps":[137,160],"only":[140,163],"if":[141,164],"LLM":[144],"judges":[145],"unanimously":[146],"agree":[147],"every":[149],"report":[150],"under":[151],"same":[153],"query,":[154],"distinguishability":[157],"assigns":[166],"at":[167,172],"least":[168,173],"one":[169,174],"majority-yes":[170],"majority-no":[175],"label":[176],"across":[177,211],"evaluated":[179],"systems.":[180],"This":[181],"process":[182],"retains":[183],"3,687":[184],"consistency-passed":[185],"rubrics,":[186],"of":[187,197,251],"2,600":[189],"remain":[190],"distinguishable":[191],"form":[193],"set":[196],"Using":[201],"set,":[205],"obtain":[207],"clearly":[208],"differentiated":[209],"rankings":[210],"10":[212],"systems,":[215],"item-level":[217],"pass":[218],"rates":[219],"ranging":[220],"58.58\\%":[222],"22.23\\%.":[224],"More":[225],"broadly,":[226],"because":[227],"removes":[230],"human-expert":[231],"execution":[232],"generation":[235],"evaluation,":[237,244],"naturally":[240],"automatic":[245],"system":[246,253],"comparison,":[247],"future":[249],"studies":[250],"evaluation-driven":[252],"improvement.":[254]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-07-16T00:00:00"}
