{"id":"https://openalex.org/W7166640827","doi":"https://doi.org/10.48550/arxiv.2606.30251","title":"TACO: Tool-Augmented Credit Optimization for Agentic Tool Use","display_name":"TACO: Tool-Augmented Credit Optimization for Agentic Tool Use","publication_year":2026,"publication_date":"2026-06-29","ids":{"openalex":"https://openalex.org/W7166640827","doi":"https://doi.org/10.48550/arxiv.2606.30251"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.30251","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.30251","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.2606.30251","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5139662737","display_name":"Mingkuan Feng","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Feng, Mingkuan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139698204","display_name":"Jinyang Wu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wu, Jinyang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139675211","display_name":"Hao Gu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gu, Hao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139710593","display_name":"Fangrui Lv","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lv, Fangrui","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139651013","display_name":"Ruihan Jin","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jin, Ruihan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5016251518","display_name":"Chuyuan Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Chuyuan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139639717","display_name":"Zhengqi Wen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wen, Zhengqi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5139651691","display_name":"Jianhua Tao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tao, Jianhua","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":0.9937999844551086,"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":0.9937999844551086,"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":0.0013000000035390258,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.000699999975040555,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/correctness","display_name":"Correctness","score":0.7042999863624573},{"id":"https://openalex.org/keywords/outcome","display_name":"Outcome (game theory)","score":0.6276999711990356},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.592199981212616},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.5626999735832214},{"id":"https://openalex.org/keywords/zero","display_name":"Zero (linguistics)","score":0.4115000069141388},{"id":"https://openalex.org/keywords/differential","display_name":"Differential (mechanical device)","score":0.3813999891281128},{"id":"https://openalex.org/keywords/action","display_name":"Action (physics)","score":0.3799999952316284}],"concepts":[{"id":"https://openalex.org/C55439883","wikidata":"https://www.wikidata.org/wiki/Q360812","display_name":"Correctness","level":2,"score":0.7042999863624573},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6653000116348267},{"id":"https://openalex.org/C148220186","wikidata":"https://www.wikidata.org/wiki/Q7111912","display_name":"Outcome (game theory)","level":2,"score":0.6276999711990356},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.592199981212616},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.5626999735832214},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4659000039100647},{"id":"https://openalex.org/C2780813799","wikidata":"https://www.wikidata.org/wiki/Q3274237","display_name":"Zero (linguistics)","level":2,"score":0.4115000069141388},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4041000008583069},{"id":"https://openalex.org/C93226319","wikidata":"https://www.wikidata.org/wiki/Q193137","display_name":"Differential (mechanical device)","level":2,"score":0.3813999891281128},{"id":"https://openalex.org/C2780791683","wikidata":"https://www.wikidata.org/wiki/Q846785","display_name":"Action (physics)","level":2,"score":0.3799999952316284},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.37470000982284546},{"id":"https://openalex.org/C43126263","wikidata":"https://www.wikidata.org/wiki/Q128751","display_name":"Source code","level":2,"score":0.37389999628067017},{"id":"https://openalex.org/C2780695315","wikidata":"https://www.wikidata.org/wiki/Q3799040","display_name":"Unobservable","level":2,"score":0.37290000915527344},{"id":"https://openalex.org/C2778334786","wikidata":"https://www.wikidata.org/wiki/Q1586270","display_name":"Variation (astronomy)","level":2,"score":0.33230000734329224},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.3084000051021576},{"id":"https://openalex.org/C2775924081","wikidata":"https://www.wikidata.org/wiki/Q55608371","display_name":"Control (management)","level":2,"score":0.3066999912261963}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.30251","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.30251","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.2606.30251","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.30251","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":0.53615403175354,"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Agentic":[0],"multimodal":[1,231],"models":[2],"perform":[3],"diverse":[4],"operations":[5,27],"on":[6,77,103,196],"an":[7,17,57,166],"image":[8],"via":[9],"code":[10,26],"and":[11,41,117,121,143,229,240],"reason":[12],"over":[13],"the":[14,110,119,122,130,152,178,182,197,205],"returned":[15],"view,":[16],"effective":[18],"paradigm":[19],"for":[20,73,134,139,145],"fine-grained":[21],"visual":[22],"question":[23],"answering.":[24],"However,":[25],"can":[28],"be":[29],"useful,":[30],"redundant,":[31],"or":[32,55],"misleading.":[33],"Outcome-only":[34],"rewards":[35,44],"cannot":[36],"precisely":[37],"distinguish":[38],"these":[39],"cases,":[40],"existing":[42,153],"process":[43],"either":[45],"fail":[46],"to":[47,51,173,204,242],"attribute":[48],"final":[49,183],"correctness":[50],"individual":[52],"tool":[53,97,210],"calls,":[54],"require":[56],"external":[58],"judge":[59],"model.":[60],"To":[61],"address":[62],"this,":[63],"we":[64],"introduce":[65],"Tool-Augmented":[66],"Credit":[67],"Optimization":[68],"(TACO),":[69],"a":[70,89,135,140,162,191,220],"GRPO":[71],"variant":[72],"code-tool":[74],"agents":[75],"built":[76],"two":[78],"coupled":[79],"advantage":[80,93,180],"channels.":[81],"The":[82,175],"first,":[83],"Differential":[84],"Answer-Probe":[85],"Reward":[86],"(DAPR),":[87],"is":[88,127,170,177],"self-supervised,":[90],"judge-free":[91],"tool-contribution":[92],"that":[94,147,234],"credits":[95],"each":[96],"call":[98],"by":[99,186],"its":[100,114,244],"own":[101],"effect":[102],"answering":[104],"correctly.":[105],"Probe":[106],"tokens":[107],"inserted":[108],"into":[109],"model's":[111],"reasoning":[112],"elicit":[113],"predictions":[115],"with":[116,156],"without":[118,212],"tool,":[120],"difference":[123,163],"in":[124],"outcome":[125,179],"reward":[126],"taken":[128],"as":[129],"call's":[131,198],"value:":[132],"positive":[133],"useful":[136],"call,":[137],"negative":[138],"misleading":[141],"one,":[142],"zero":[144],"one":[146],"changes":[148],"nothing.":[149],"This":[150],"reuses":[151],"answer":[154],"checker":[155],"no":[157],"auxiliary":[158],"judge,":[159],"and,":[160],"being":[161],"rather":[164],"than":[165],"absolute":[167],"probe":[168],"score,":[169],"naturally":[171],"robust":[172],"probe-hacking.":[174],"second":[176],"from":[181],"answer,":[184],"distributed":[185],"Outcome-Gated":[187],"Advantage":[188],"Routing":[189],"(OGAR):":[190],"parameter-free":[192],"rule":[193],"that,":[194],"conditioned":[195],"outcome,":[199],"delivers":[200],"this":[201],"credit":[202],"only":[203,246],"responsible":[206],"segments,":[207],"suppressing":[208],"wasted":[209],"calls":[211],"any":[213],"cost":[214],"term.":[215],"We":[216],"train":[217],"TACO":[218],"through":[219],"two-stage":[221],"SFT+RL":[222],"pipeline.":[223],"Extensive":[224],"experiments":[225],"across":[226],"perception,":[227],"reasoning,":[228],"general":[230],"benchmarks":[232],"show":[233],"it":[235],"yields":[236],"consistent":[237],"accuracy":[238],"gains":[239],"learns":[241],"invoke":[243],"tools":[245],"when":[247],"they":[248],"help.":[249]},"counts_by_year":[],"updated_date":"2026-07-01T06:29:00.853634","created_date":"2026-07-01T00:00:00"}