{"id":"https://openalex.org/W7163140514","doi":"https://doi.org/10.48550/arxiv.2606.02132","title":"Learning When Not to Act: Mitigating Tool Abuse in Agentic Reinforcement Learning","display_name":"Learning When Not to Act: Mitigating Tool Abuse in Agentic Reinforcement Learning","publication_year":2026,"publication_date":"2026-06-01","ids":{"openalex":"https://openalex.org/W7163140514","doi":"https://doi.org/10.48550/arxiv.2606.02132"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.02132","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.02132","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.2606.02132","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5058244529","display_name":"Liuji Chen","orcid":"https://orcid.org/0000-0001-7636-6031"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Liuji","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137649379","display_name":"Dianxing Tang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tang, Dianxing","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137664366","display_name":"Xing Shi","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shi, Xing","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137665301","display_name":"Dingshuo Chen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Dingshuo","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137710430","display_name":"Qiang Liu","orcid":"https://orcid.org/0000-0002-9479-4141"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Qiang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137688703","display_name":"Shu Wu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wu, Shu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5137691301","display_name":"Liang Wang","orcid":"https://orcid.org/0000-0002-3995-9097"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Liang","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/T11704","display_name":"Mobile Crowdsensing and Crowdsourcing","score":0.21789999306201935,"subfield":{"id":"https://openalex.org/subfields/1706","display_name":"Computer Science Applications"},"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/T11704","display_name":"Mobile Crowdsensing and Crowdsourcing","score":0.21789999306201935,"subfield":{"id":"https://openalex.org/subfields/1706","display_name":"Computer Science Applications"},"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/T10462","display_name":"Reinforcement Learning in Robotics","score":0.1770000010728836,"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":0.06750000268220901,"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/reinforcement-learning","display_name":"Reinforcement learning","score":0.7075999975204468},{"id":"https://openalex.org/keywords/reinforcement","display_name":"Reinforcement","score":0.46540001034736633},{"id":"https://openalex.org/keywords/policy-learning","display_name":"Policy learning","score":0.40799999237060547},{"id":"https://openalex.org/keywords/proactive-learning","display_name":"Proactive learning","score":0.3292999863624573},{"id":"https://openalex.org/keywords/error-driven-learning","display_name":"Error-driven learning","score":0.288100004196167}],"concepts":[{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.7075999975204468},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6179999709129333},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4690999984741211},{"id":"https://openalex.org/C67203356","wikidata":"https://www.wikidata.org/wiki/Q1321905","display_name":"Reinforcement","level":2,"score":0.46540001034736633},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.42489999532699585},{"id":"https://openalex.org/C2779436431","wikidata":"https://www.wikidata.org/wiki/Q30672407","display_name":"Policy learning","level":2,"score":0.40799999237060547},{"id":"https://openalex.org/C12298181","wikidata":"https://www.wikidata.org/wiki/Q7246814","display_name":"Proactive learning","level":5,"score":0.3292999863624573},{"id":"https://openalex.org/C47932503","wikidata":"https://www.wikidata.org/wiki/Q5395689","display_name":"Error-driven learning","level":3,"score":0.288100004196167},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.2872999906539917},{"id":"https://openalex.org/C112972136","wikidata":"https://www.wikidata.org/wiki/Q7595718","display_name":"Stability (learning theory)","level":2,"score":0.28600001335144043},{"id":"https://openalex.org/C79416737","wikidata":"https://www.wikidata.org/wiki/Q2305519","display_name":"Social learning","level":2,"score":0.28119999170303345},{"id":"https://openalex.org/C48145219","wikidata":"https://www.wikidata.org/wiki/Q1335365","display_name":"Security token","level":2,"score":0.2572000026702881},{"id":"https://openalex.org/C180747234","wikidata":"https://www.wikidata.org/wiki/Q23373","display_name":"Cognitive psychology","level":1,"score":0.250900000333786}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.02132","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.02132","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.2606.02132","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.02132","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":[{"id":"https://metadata.un.org/sdg/16","score":0.5729227662086487,"display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Agentic":[0,47],"reinforcement":[1],"learning":[2],"can":[3,133],"induce":[4],"tool":[5,33,54,71,120],"abuse,":[6],"where":[7],"models":[8],"overuse":[9],"external":[10],"tools":[11,139],"even":[12],"for":[13],"queries":[14],"solvable":[15],"by":[16,112,122],"internal":[17],"reasoning.":[18,143],"Existing":[19],"approaches":[20],"mitigate":[21],"this":[22],"issue":[23],"with":[24,106],"uniform":[25],"tool-use":[26],"penalties":[27],"or":[28],"hard":[29],"limits,":[30],"which":[31],"reduce":[32],"frequency":[34],"but":[35],"may":[36],"also":[37],"suppress":[38],"useful":[39],"tool-assisted":[40],"exploration.":[41],"We":[42],"propose":[43],"EAPO,":[44],"an":[45],"Efficient":[46],"Policy":[48],"Optimization":[49],"framework":[50],"that":[51,131],"learns":[52],"selective":[53],"use.":[55],"EAPO":[56,93,108],"introduces":[57],"tool-free":[58],"trajectories":[59],"into":[60],"each":[61],"rollout":[62],"group,":[63],"applies":[64],"difficulty-aware":[65],"reward":[66],"shaping":[67],"to":[68,82,137],"penalize":[69],"redundant":[70],"calls":[72,121],"mainly":[73],"on":[74,100],"easier":[75],"queries,":[76],"and":[77,89,103,115,125],"uses":[78],"confidence-aware":[79],"token":[80],"reweighting":[81],"improve":[83],"policy":[84],"learning.":[85],"Across":[86],"nine":[87],"mathematical":[88],"knowledge-intensive":[90],"reasoning":[91],"benchmarks,":[92],"consistently":[94],"improves":[95,109],"the":[96],"accuracy":[97],"efficiency":[98],"trade-off":[99],"Qwen2.5-3B,":[101],"Qwen2.5-7B,":[102],"Llama3.1-8B.":[104],"Compared":[105],"GRPO,":[107],"average":[110,119],"performance":[111],"10.45%,":[113],"7.27%,":[114],"9.69%,":[116],"while":[117],"reducing":[118],"18.33%,":[123,124],"24.59%,":[126],"respectively.":[127],"These":[128],"results":[129],"show":[130],"agents":[132],"learn":[134],"when":[135],"not":[136],"use":[138],"without":[140],"compromising":[141],"tool-integrated":[142]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-06-03T00:00:00"}
