{"id":"https://openalex.org/W7154381004","doi":"https://doi.org/10.48550/arxiv.2604.10015","title":"FinTrace: Holistic Trajectory-Level Evaluation of LLM Tool Calling for Long-Horizon Financial Tasks","display_name":"FinTrace: Holistic Trajectory-Level Evaluation of LLM Tool Calling for Long-Horizon Financial Tasks","publication_year":2026,"publication_date":"2026-04-11","ids":{"openalex":"https://openalex.org/W7154381004","doi":"https://doi.org/10.48550/arxiv.2604.10015"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.10015","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.10015","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":null,"license_id":null,"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.2604.10015","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5133563959","display_name":"Yupeng Cao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Cao, Yupeng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133561569","display_name":"Haohang Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Haohang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133577199","display_name":"Weijin Liu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Weijin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5121067079","display_name":"Wenbo Cao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Cao, Wenbo","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133601762","display_name":"Anke Xu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xu, Anke","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133556556","display_name":"Lingfei Qian","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Qian, Lingfei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133569120","display_name":"Xueqing Peng","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Peng, Xueqing","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133622790","display_name":"Minxue Tang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tang, Minxue","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5122051492","display_name":"Zhiyuan Yao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yao, Zhiyuan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133620086","display_name":"Jimin Huang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Huang, Jimin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133568960","display_name":"K. P. Subbalakshmi","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Subbalakshmi, K. P.","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133583983","display_name":"Zining Zhu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhu, Zining","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133603586","display_name":"Jordan W. Suchow","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Suchow, Jordan W.","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5133601138","display_name":"Yangyang Yu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yu, Yangyang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":14,"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/T10028","display_name":"Topic Modeling","score":0.296099990606308,"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/T10028","display_name":"Topic Modeling","score":0.296099990606308,"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/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.07810000330209732,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.04820000007748604,"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/construct","display_name":"Construct (python library)","score":0.6182000041007996},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.6152999997138977},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5900999903678894},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5623999834060669},{"id":"https://openalex.org/keywords/preference","display_name":"Preference","score":0.5491999983787537},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.5274999737739563},{"id":"https://openalex.org/keywords/action","display_name":"Action (physics)","score":0.45210000872612}],"concepts":[{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.6182000041007996},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6152999997138977},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6090999841690063},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5900999903678894},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5623999834060669},{"id":"https://openalex.org/C2781249084","wikidata":"https://www.wikidata.org/wiki/Q908656","display_name":"Preference","level":2,"score":0.5491999983787537},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.5274999737739563},{"id":"https://openalex.org/C2780791683","wikidata":"https://www.wikidata.org/wiki/Q846785","display_name":"Action (physics)","level":2,"score":0.45210000872612},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.4453999996185303},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.44029998779296875},{"id":"https://openalex.org/C10138342","wikidata":"https://www.wikidata.org/wiki/Q43015","display_name":"Finance","level":1,"score":0.42820000648498535},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.39469999074935913},{"id":"https://openalex.org/C2780385302","wikidata":"https://www.wikidata.org/wiki/Q367158","display_name":"Protocol (science)","level":3,"score":0.32910001277923584},{"id":"https://openalex.org/C139043278","wikidata":"https://www.wikidata.org/wiki/Q837171","display_name":"Financial services","level":2,"score":0.31779998540878296},{"id":"https://openalex.org/C2777868144","wikidata":"https://www.wikidata.org/wiki/Q7239817","display_name":"Preference elicitation","level":3,"score":0.30059999227523804},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.27489998936653137},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.27079999446868896},{"id":"https://openalex.org/C56739046","wikidata":"https://www.wikidata.org/wiki/Q192060","display_name":"Knowledge management","level":1,"score":0.25920000672340393},{"id":"https://openalex.org/C148220186","wikidata":"https://www.wikidata.org/wiki/Q7111912","display_name":"Outcome (game theory)","level":2,"score":0.2587999999523163}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.10015","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.10015","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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2604.10015","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.10015","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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"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":{"Recent":[0],"studies":[1],"demonstrate":[2],"that":[3,39,106,178,202],"tool-calling":[4,98],"capability":[5],"enables":[6],"large":[7],"language":[8],"models":[9,109,115],"(LLMs)":[10],"to":[11,41,210],"interact":[12],"with":[13,75,117,158,187],"external":[14],"environments":[15],"for":[16,151],"long-horizon":[17],"financial":[18,26,62,152],"tasks.":[19],"While":[20],"existing":[21],"benchmarks":[22],"have":[23],"begun":[24],"evaluating":[25],"tool":[27,112],"calling,":[28],"they":[29],"focus":[30],"on":[31,36,180],"limited":[32],"scenarios":[33],"and":[34,89,120,133,161,176],"rely":[35],"call-level":[37],"metrics":[38,77],"fail":[40],"capture":[42],"trajectory-level":[43,148,203],"reasoning":[44,134,185],"quality.":[45,213],"To":[46,139],"address":[47],"this":[48],"gap,":[49],"we":[50,143],"introduce":[51],"FinTrace,":[52],"a":[53,71,125,199],"benchmark":[54],"comprising":[55],"800":[56],"expert-annotated":[57],"trajectories":[58,157],"spanning":[59],"34":[60],"real-world":[61],"task":[63],"categories":[64],"across":[65],"multiple":[66],"difficulty":[67],"levels.":[68],"FinTrace":[69],"employs":[70],"rubric-based":[72],"evaluation":[73,101],"protocol":[74],"nine":[76],"organized":[78],"along":[79],"four":[80],"axes":[81],"--":[82,92],"action":[83],"correctness,":[84],"execution":[85],"efficiency,":[86],"process":[87],"quality,":[88,123],"output":[90,212],"quality":[91,197],"enabling":[93],"fine-grained":[94],"assessment":[95],"of":[96,102],"LLM":[97],"behavior.":[99],"Our":[100],"13":[103],"LLMs":[104],"reveals":[105],"while":[107],"frontier":[108],"achieve":[110],"strong":[111],"selection,":[113],"all":[114],"struggle":[116],"information":[118],"utilization":[119],"final":[121,211],"answer":[122,196],"exposing":[124],"critical":[126],"gap":[127],"between":[128],"invoking":[129],"the":[130,146],"right":[131],"tools":[132],"effectively":[135,190],"over":[136],"their":[137],"outputs.":[138],"move":[140],"beyond":[141],"diagnosis,":[142],"construct":[144],"FinTrace-Training,":[145],"first":[147],"preference":[149,162,173],"dataset":[150],"tool-calling,":[153],"containing":[154],"8,196":[155],"curated":[156],"tool-augmented":[159],"contexts":[160],"pairs.":[163],"We":[164],"fine-tune":[165],"Qwen-3.5-9B":[166],"using":[167],"supervised":[168],"fine-tuning":[169],"followed":[170],"by":[171],"direct":[172],"optimization":[174],"(DPO)":[175],"show":[177],"training":[179],"FinTrace-Training":[181],"consistently":[182],"improves":[183],"intermediate":[184],"metrics,":[186],"DPO":[188],"more":[189],"suppressing":[191],"failure":[192],"modes.":[193],"However,":[194],"end-to-end":[195],"remains":[198],"bottleneck,":[200],"indicating":[201],"improvements":[204],"do":[205],"not":[206],"yet":[207],"fully":[208],"propagate":[209]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-04-15T00:00:00"}
