{"id":"https://openalex.org/W7125243857","doi":"https://doi.org/10.48550/arxiv.2601.13284","title":"Balancing Classification and Calibration Performance in Decision-Making LLMs via Calibration Aware Reinforcement Learning","display_name":"Balancing Classification and Calibration Performance in Decision-Making LLMs via Calibration Aware Reinforcement Learning","publication_year":2026,"publication_date":"2026-01-19","ids":{"openalex":"https://openalex.org/W7125243857","doi":"https://doi.org/10.48550/arxiv.2601.13284"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2601.13284","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2601.13284","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":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2601.13284","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5006513684","display_name":"Duygu Nur Yaldiz","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Yaldiz, Duygu Nur","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5055466746","display_name":"Evangelia Spiliopoulou","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Spiliopoulou, Evangelia","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5032213389","display_name":"Qi Zheng","orcid":"https://orcid.org/0000-0002-5622-5079"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Qi, Zheng","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040172025","display_name":"Siddharth Varia","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Varia, Siddharth","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5123490848","display_name":"Srikanth Doss","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Doss, Srikanth","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":null,"display_name":"Pappas, Nikolaos","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Pappas, Nikolaos","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5006513684"],"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/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.5855000019073486,"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/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.5855000019073486,"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/T10028","display_name":"Topic Modeling","score":0.07190000265836716,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.0575999990105629,"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/reinforcement-learning","display_name":"Reinforcement learning","score":0.8611999750137329},{"id":"https://openalex.org/keywords/calibration","display_name":"Calibration","score":0.8057000041007996},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.619700014591217},{"id":"https://openalex.org/keywords/reinforcement","display_name":"Reinforcement","score":0.5885999798774719},{"id":"https://openalex.org/keywords/verifiable-secret-sharing","display_name":"Verifiable secret sharing","score":0.5099999904632568},{"id":"https://openalex.org/keywords/downstream","display_name":"Downstream (manufacturing)","score":0.3684999942779541},{"id":"https://openalex.org/keywords/meta-learning","display_name":"Meta learning (computer science)","score":0.3434999883174896}],"concepts":[{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.8611999750137329},{"id":"https://openalex.org/C165838908","wikidata":"https://www.wikidata.org/wiki/Q736777","display_name":"Calibration","level":2,"score":0.8057000041007996},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7214999794960022},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.619700014591217},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6193000078201294},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6089000105857849},{"id":"https://openalex.org/C67203356","wikidata":"https://www.wikidata.org/wiki/Q1321905","display_name":"Reinforcement","level":2,"score":0.5885999798774719},{"id":"https://openalex.org/C85847156","wikidata":"https://www.wikidata.org/wiki/Q59015987","display_name":"Verifiable secret sharing","level":3,"score":0.5099999904632568},{"id":"https://openalex.org/C2776207758","wikidata":"https://www.wikidata.org/wiki/Q5303302","display_name":"Downstream (manufacturing)","level":2,"score":0.3684999942779541},{"id":"https://openalex.org/C2781002164","wikidata":"https://www.wikidata.org/wiki/Q6822311","display_name":"Meta learning (computer science)","level":3,"score":0.3434999883174896},{"id":"https://openalex.org/C44249647","wikidata":"https://www.wikidata.org/wiki/Q208498","display_name":"Confidence interval","level":2,"score":0.3391999900341034},{"id":"https://openalex.org/C2776299755","wikidata":"https://www.wikidata.org/wiki/Q432449","display_name":"Carry (investment)","level":2,"score":0.31189998984336853},{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.3068999946117401},{"id":"https://openalex.org/C59594135","wikidata":"https://www.wikidata.org/wiki/Q5249242","display_name":"Decision model","level":2,"score":0.28949999809265137},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2757999897003174},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.26570001244544983},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.26409998536109924},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.2623000144958496},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.2556999921798706}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2601.13284","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2601.13284","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":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2601.13284","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2601.13284","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":"article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","score":0.8048132061958313,"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":{"Large":[0],"language":[1],"models":[2],"(LLMs)":[3],"are":[4,19],"increasingly":[5],"deployed":[6],"in":[7,50,112],"decision-making":[8],"tasks,":[9],"where":[10],"not":[11,117],"only":[12],"accuracy":[13,149],"but":[14],"also":[15],"reliable":[16],"confidence":[17,22,119],"estimates":[18],"essential.":[20],"Well-calibrated":[21],"enables":[23],"downstream":[24],"systems":[25],"to":[26,29,35,37,158],"decide":[27],"when":[28,34],"trust":[30],"a":[31,45,135],"model":[32],"and":[33,59,115],"defer":[36],"fallback":[38],"mechanisms.":[39],"In":[40],"this":[41,131],"work,":[42],"we":[43,97,133],"conduct":[44],"systematic":[46],"study":[47],"of":[48,109],"calibration":[49],"two":[51],"widely":[52],"used":[53],"fine-tuning":[54,57],"paradigms:":[55],"supervised":[56],"(SFT)":[58],"reinforcement":[60,123,137],"learning":[61,124,138],"with":[62,90],"verifiable":[63],"rewards":[64],"(RLVR).":[65],"We":[66],"show":[67],"that":[68,102,140],"while":[69,151],"RLVR":[70],"improves":[71],"task":[72],"performance,":[73],"it":[74],"produces":[75],"extremely":[76],"overconfident":[77],"models,":[78],"whereas":[79],"SFT":[80],"yields":[81],"substantially":[82],"better":[83],"calibration,":[84],"even":[85],"under":[86],"distribution":[87],"shift,":[88],"though":[89],"smaller":[91],"performance":[92],"gains.":[93],"Through":[94],"targeted":[95],"experiments,":[96],"diagnose":[98],"RLVR's":[99,148],"failure,":[100],"showing":[101],"decision":[103,111],"tokens":[104],"act":[105],"as":[106],"extraction":[107],"steps":[108],"the":[110],"reasoning":[113],"traces":[114],"do":[116],"carry":[118],"information,":[120],"which":[121],"prevents":[122],"from":[125],"surfacing":[126],"calibrated":[127],"alternatives.":[128],"Based":[129],"on":[130],"insight,":[132],"propose":[134],"calibration-aware":[136],"formulation":[139],"directly":[141],"adjusts":[142],"decision-token":[143],"probabilities.":[144],"Our":[145],"method":[146],"preserves":[147],"level":[150],"mitigating":[152],"overconfidence,":[153],"reducing":[154],"ECE":[155],"scores":[156],"up":[157],"9":[159],"points.":[160]},"counts_by_year":[],"updated_date":"2026-03-25T23:56:10.502304","created_date":"2026-01-22T00:00:00"}
