{"id":"https://openalex.org/W7154170311","doi":"https://doi.org/10.48550/arxiv.2604.09455","title":"E3-TIR: Enhanced Experience Exploitation for Tool-Integrated Reasoning","display_name":"E3-TIR: Enhanced Experience Exploitation for Tool-Integrated Reasoning","publication_year":2026,"publication_date":"2026-04-10","ids":{"openalex":"https://openalex.org/W7154170311","doi":"https://doi.org/10.48550/arxiv.2604.09455"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.09455","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.09455","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":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2604.09455","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5102723985","display_name":"Wei Guo","orcid":"https://orcid.org/0000-0003-4257-1453"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Guo, Weiyang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133479769","display_name":"Zesheng Shi","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shi, Zesheng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5122276255","display_name":"Liye Zhao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhao, Liye","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133495377","display_name":"Jiayuan Ma","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ma, Jiayuan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133535463","display_name":"Zeen Zhu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhu, Zeen","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133548413","display_name":"Junxian He","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"He, Junxian","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101484485","display_name":"Min Zhang","orcid":"https://orcid.org/0000-0002-8130-5214"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Min","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5101460677","display_name":"Jing Li","orcid":"https://orcid.org/0000-0001-8095-0425"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Jing","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":0.17949999868869781,"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":0.17949999868869781,"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":0.179299995303154,"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":0.1737000048160553,"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/metric","display_name":"Metric (unit)","score":0.47679999470710754},{"id":"https://openalex.org/keywords/expert-system","display_name":"Expert system","score":0.37560001015663147},{"id":"https://openalex.org/keywords/face","display_name":"Face (sociological concept)","score":0.37290000915527344},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.35260000824928284},{"id":"https://openalex.org/keywords/training","display_name":"Training (meteorology)","score":0.3504999876022339},{"id":"https://openalex.org/keywords/performance-metric","display_name":"Performance metric","score":0.3440999984741211}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7312999963760376},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.48910000920295715},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.47679999470710754},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4440999925136566},{"id":"https://openalex.org/C58328972","wikidata":"https://www.wikidata.org/wiki/Q184609","display_name":"Expert system","level":2,"score":0.37560001015663147},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.37290000915527344},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.35260000824928284},{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.3504999876022339},{"id":"https://openalex.org/C2780898871","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Performance metric","level":2,"score":0.3440999984741211},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.33329999446868896},{"id":"https://openalex.org/C105002631","wikidata":"https://www.wikidata.org/wiki/Q4833645","display_name":"Subject-matter expert","level":3,"score":0.3255000114440918},{"id":"https://openalex.org/C48677424","wikidata":"https://www.wikidata.org/wiki/Q6888088","display_name":"Mode (computer interface)","level":2,"score":0.2953999936580658},{"id":"https://openalex.org/C112930515","wikidata":"https://www.wikidata.org/wiki/Q4389547","display_name":"Risk analysis (engineering)","level":1,"score":0.29280000925064087},{"id":"https://openalex.org/C2780598303","wikidata":"https://www.wikidata.org/wiki/Q65921492","display_name":"Flexibility (engineering)","level":2,"score":0.2897000014781952},{"id":"https://openalex.org/C56739046","wikidata":"https://www.wikidata.org/wiki/Q192060","display_name":"Knowledge management","level":1,"score":0.27649998664855957},{"id":"https://openalex.org/C137836250","wikidata":"https://www.wikidata.org/wiki/Q984063","display_name":"Optimization problem","level":2,"score":0.2678000032901764},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.26100000739097595},{"id":"https://openalex.org/C2781316041","wikidata":"https://www.wikidata.org/wiki/Q1230584","display_name":"Diversity (politics)","level":2,"score":0.2572000026702881}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.09455","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.09455","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":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2604.09455","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.09455","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":"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":{"While":[0],"Large":[1],"Language":[2],"Models":[3],"(LLMs)":[4],"have":[5],"demonstrated":[6],"significant":[7,17],"potential":[8],"in":[9,155],"Tool-Integrated":[10],"Reasoning":[11],"(TIR),":[12],"existing":[13],"training":[14,72,128,167],"paradigms":[15,141],"face":[16],"limitations:":[18],"Zero-RL":[19],"suffers":[20],"from":[21,112],"inefficient":[22],"exploration":[23,91,125],"and":[24,42,85,95,107,166],"mode":[25],"degradation":[26],"due":[27],"to":[28,175],"a":[29,59,97,135,159,171],"lack":[30],"of":[31,66,77,150,157],"prior":[32],"guidance,":[33],"while":[34,145],"SFT-then-RL":[35],"is":[36,178],"limited":[37],"by":[38,46],"high":[39],"data":[40,164],"costs":[41],"capability":[43],"plateaus":[44],"caused":[45],"low-entropy":[47],"collapse.":[48],"To":[49],"address":[50],"these":[51],"challenges,":[52],"we":[53,70,102,169],"propose":[54],"E3-TIR":[55,133],"(Enhanced":[56],"Experience":[57],"Exploitation),":[58],"warm-up":[60],"paradigm":[61],"for":[62],"the":[63,74,119,151],"early":[64],"stages":[65],"agent":[67],"training.":[68],"Specifically,":[69],"formulate":[71],"as":[73],"dynamic":[75],"integration":[76],"three":[78],"experience":[79],"types:":[80],"Expert":[81,83],"Prefixes,":[82],"Guided,":[84],"Self-Exploration.":[86],"By":[87],"executing":[88],"diverse":[89],"branching":[90],"around":[92],"expert":[93],"\"anchors\"":[94],"employing":[96],"mix":[98],"policy":[99],"optimization":[100,109],"mechanism,":[101],"effectively":[103,123],"mitigate":[104],"distribution":[105],"shifts":[106],"resolve":[108],"conflicts":[110],"arising":[111],"shared":[113],"prefixes.":[114],"Our":[115],"method":[116],"dynamically":[117],"adapts":[118],"model's":[120],"knowledge":[121],"boundaries,":[122],"balancing":[124],"diversity":[126],"with":[127],"efficiency.Experimental":[129],"results":[130],"demonstrate":[131],"that":[132],"achieves":[134],"6":[136],"performance":[137],"improvement":[138],"over":[139],"traditional":[140],"on":[142],"tool-use":[143],"tasks,":[144],"requiring":[146],"less":[147],"than":[148],"10":[149],"synthetic":[152],"data.":[153],"Furthermore,":[154],"terms":[156],"ROI,":[158],"comprehensive":[160],"metric":[161],"integrating":[162],"performance,":[163],"cost,":[165],"efficiency":[168],"achieve":[170],"1.46x":[172],"gain":[173],"compared":[174],"baselines.":[176],"Code":[177],"available":[179],"at":[180],"https://github.com/yuki-younai/E3-TIR.":[181]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-04-14T00:00:00"}