{"id":"https://openalex.org/W4417118038","doi":"https://doi.org/10.48550/arxiv.2506.06395","title":"Confidence Is All You Need: Few-Shot RL Fine-Tuning of Language Models","display_name":"Confidence Is All You Need: Few-Shot RL Fine-Tuning of Language Models","publication_year":2025,"publication_date":"2025-06-05","ids":{"openalex":"https://openalex.org/W4417118038","doi":"https://doi.org/10.48550/arxiv.2506.06395"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2506.06395","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2506.06395","pdf_url":"https://arxiv.org/pdf/2506.06395","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2506.06395","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5076957254","display_name":"Pengyi Li","orcid":"https://orcid.org/0009-0009-8546-2346"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Pengyi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5095335184","display_name":"Matvey Skripkin","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Skripkin, Matvey","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5120754255","display_name":"Alexander Zubrey","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zubrey, Alexander","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101915268","display_name":"Andrey Kuznetsov","orcid":"https://orcid.org/0000-0002-0425-2171"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kuznetsov, Andrey","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5004111307","display_name":"Ivan Oseledets","orcid":"https://orcid.org/0000-0003-2071-2163"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Oseledets, Ivan","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/T10028","display_name":"Topic Modeling","score":0.3407000005245209,"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":0.3407000005245209,"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":0.12200000137090683,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.07479999959468842,"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":0.6959999799728394},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.6141999959945679},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5910000205039978},{"id":"https://openalex.org/keywords/preference","display_name":"Preference","score":0.5224999785423279},{"id":"https://openalex.org/keywords/language-model","display_name":"Language model","score":0.5203999876976013},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.412200003862381},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.3887999951839447},{"id":"https://openalex.org/keywords/language-understanding","display_name":"Language understanding","score":0.3874000012874603}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7221999764442444},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.6959999799728394},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.670799970626831},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.6141999959945679},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5910000205039978},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.574400007724762},{"id":"https://openalex.org/C2781249084","wikidata":"https://www.wikidata.org/wiki/Q908656","display_name":"Preference","level":2,"score":0.5224999785423279},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.5203999876976013},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.5141000151634216},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.412200003862381},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.3887999951839447},{"id":"https://openalex.org/C2983448237","wikidata":"https://www.wikidata.org/wiki/Q1078276","display_name":"Language understanding","level":2,"score":0.3874000012874603},{"id":"https://openalex.org/C181204326","wikidata":"https://www.wikidata.org/wiki/Q7239820","display_name":"Preference learning","level":3,"score":0.38580000400543213},{"id":"https://openalex.org/C67203356","wikidata":"https://www.wikidata.org/wiki/Q1321905","display_name":"Reinforcement","level":2,"score":0.3833000063896179},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.29989999532699585},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.2994999885559082},{"id":"https://openalex.org/C74672266","wikidata":"https://www.wikidata.org/wiki/Q815859","display_name":"Language acquisition","level":2,"score":0.29899999499320984},{"id":"https://openalex.org/C195324797","wikidata":"https://www.wikidata.org/wiki/Q33742","display_name":"Natural language","level":2,"score":0.28369998931884766},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.2782000005245209},{"id":"https://openalex.org/C2777868144","wikidata":"https://www.wikidata.org/wiki/Q7239817","display_name":"Preference elicitation","level":3,"score":0.2678999900817871},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.25119999051094055}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2506.06395","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2506.06395","pdf_url":"https://arxiv.org/pdf/2506.06395","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2506.06395","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2506.06395","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":"pmh:oai:arXiv.org:2506.06395","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2506.06395","pdf_url":"https://arxiv.org/pdf/2506.06395","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"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":{"Large":[0],"language":[1],"models":[2],"(LLMs)":[3],"excel":[4],"at":[5],"reasoning,":[6],"yet":[7],"post-training":[8,99],"remains":[9],"critical":[10],"for":[11,51,101],"aligning":[12],"their":[13],"behavior":[14],"with":[15,61],"task":[16],"goals.":[17],"Existing":[18],"reinforcement":[19],"learning":[20],"(RL)":[21],"methods":[22],"often":[23],"depend":[24],"on":[25,78,81,84,88,92],"costly":[26],"human":[27],"annotations":[28],"or":[29,55,69],"external":[30],"reward":[31,47,56],"models.":[32],"We":[33],"propose":[34],"Reinforcement":[35],"Learning":[36],"via":[37],"Self-Confidence":[38],"(RLSC),":[39],"which":[40],"uses":[41],"the":[42,49],"model's":[43],"own":[44],"confidence":[45],"as":[46],"signals-eliminating":[48],"need":[50],"labels,":[52],"preference":[53],"models,":[54,103],"engineering.":[57],"Applied":[58],"to":[59],"Qwen2.5-Math-7B":[60],"only":[62,105],"16":[63],"samples":[64,110],"per":[65],"question":[66],"and":[67,90,111],"10":[68],"20":[70],"training":[71],"steps,":[72],"RLSC":[73,94],"improves":[74],"accuracy":[75],"by":[76],"+13.4%":[77],"AIME2024,":[79],"+21.2%":[80],"MATH500,":[82],"+21.7%":[83],"Minerva":[85],"Math,":[86],"+20.8%":[87],"Olympiadbench,":[89],"+9.7%":[91],"AMC23.":[93],"provides":[95],"a":[96,106],"simple,":[97],"scalable":[98],"method":[100],"inference":[102],"requiring":[104],"small":[107],"number":[108],"of":[109],"unlabelled":[112],"supervision.":[113]},"counts_by_year":[],"updated_date":"2026-08-26T07:47:46.906454","created_date":"2025-10-10T00:00:00"}