{"id":"https://openalex.org/W7162392775","doi":"https://doi.org/10.48550/arxiv.2605.24331","title":"CurveRL: Principled Distribution-Aware Context Reweighting for LLM Reasoning","display_name":"CurveRL: Principled Distribution-Aware Context Reweighting for LLM Reasoning","publication_year":2026,"publication_date":"2026-05-23","ids":{"openalex":"https://openalex.org/W7162392775","doi":"https://doi.org/10.48550/arxiv.2605.24331"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.24331","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.24331","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.2605.24331","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5137078210","display_name":"Ke Sun","orcid":"https://orcid.org/0000-0003-0425-7754"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sun, Ke","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137073178","display_name":"Yizhou Zhao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhao, Yizhou","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137067458","display_name":"Jiayi Xin","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xin, Jiayi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137031905","display_name":"Qi Long","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Long, Qi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5137002877","display_name":"Weijie Su","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Su, Weijie","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/T10462","display_name":"Reinforcement Learning in Robotics","score":0.27489998936653137,"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/T10462","display_name":"Reinforcement Learning in Robotics","score":0.27489998936653137,"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":0.12219999730587006,"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/T12031","display_name":"Speech and dialogue systems","score":0.1185000017285347,"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/context","display_name":"Context (archaeology)","score":0.6251000165939331},{"id":"https://openalex.org/keywords/weighting","display_name":"Weighting","score":0.5943999886512756},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.5078999996185303},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.5058000087738037},{"id":"https://openalex.org/keywords/rank","display_name":"Rank (graph theory)","score":0.4456000030040741},{"id":"https://openalex.org/keywords/value","display_name":"Value (mathematics)","score":0.3743000030517578},{"id":"https://openalex.org/keywords/quantile","display_name":"Quantile","score":0.36559998989105225}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6717000007629395},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.6251000165939331},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6083999872207642},{"id":"https://openalex.org/C183115368","wikidata":"https://www.wikidata.org/wiki/Q856577","display_name":"Weighting","level":2,"score":0.5943999886512756},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.5078999996185303},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.5058000087738037},{"id":"https://openalex.org/C164226766","wikidata":"https://www.wikidata.org/wiki/Q7293202","display_name":"Rank (graph theory)","level":2,"score":0.4456000030040741},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4410000145435333},{"id":"https://openalex.org/C2776291640","wikidata":"https://www.wikidata.org/wiki/Q2912517","display_name":"Value (mathematics)","level":2,"score":0.3743000030517578},{"id":"https://openalex.org/C118671147","wikidata":"https://www.wikidata.org/wiki/Q578714","display_name":"Quantile","level":2,"score":0.36559998989105225},{"id":"https://openalex.org/C2775924081","wikidata":"https://www.wikidata.org/wiki/Q55608371","display_name":"Control (management)","level":2,"score":0.36390000581741333},{"id":"https://openalex.org/C14646407","wikidata":"https://www.wikidata.org/wiki/Q1430750","display_name":"Bellman equation","level":2,"score":0.34689998626708984},{"id":"https://openalex.org/C107524782","wikidata":"https://www.wikidata.org/wiki/Q40164","display_name":"Lever","level":2,"score":0.3452000021934509},{"id":"https://openalex.org/C112972136","wikidata":"https://www.wikidata.org/wiki/Q7595718","display_name":"Stability (learning theory)","level":2,"score":0.337799996137619},{"id":"https://openalex.org/C197055811","wikidata":"https://www.wikidata.org/wiki/Q207522","display_name":"Probability density function","level":2,"score":0.310699999332428},{"id":"https://openalex.org/C2778334786","wikidata":"https://www.wikidata.org/wiki/Q1586270","display_name":"Variation (astronomy)","level":2,"score":0.30709999799728394},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.26820001006126404},{"id":"https://openalex.org/C28901747","wikidata":"https://www.wikidata.org/wiki/Q177571","display_name":"Decision theory","level":2,"score":0.26109999418258667}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.24331","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.24331","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.2605.24331","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.24331","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":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Context":[0],"or":[1],"prompt-level":[2],"reweighting":[3,46,84],"has":[4],"emerged":[5],"as":[6,47,152],"a":[7,48,52,62,81,90,153],"central":[8],"algorithmic":[9],"lever":[10],"in":[11,56,94,126,167],"Reinforcement":[12],"Learning":[13],"with":[14],"Verified":[15],"Rewards":[16],"(RLVR)":[17],"for":[18,156],"improving":[19],"the":[20,28,57,96,105,119,123,127],"reasoning":[21],"capability":[22],"of":[23,51,108,122],"large":[24],"language":[25],"models,":[26],"yet":[27],"principle":[29],"determining":[30],"what":[31],"constitutes":[32],"an":[33],"optimal":[34],"weighting":[35],"remains":[36],"poorly":[37],"understood.":[38],"We":[39],"address":[40],"this":[41,76],"gap":[42],"by":[43],"formulating":[44],"prompt":[45,83,101],"functional":[49,54],"derivative":[50],"utility":[53],"defined":[55],"pass-rate":[58],"function":[59],"space,":[60],"yielding":[61],"unified":[63],"optimality":[64,77],"framework":[65],"that":[66,136],"accommodates":[67],"existing":[68],"schemes,":[69],"including":[70],"REINFORCE":[71],"and":[72,115,143,158],"GRPO.":[73],"Building":[74],"on":[75,89,104,112],"framework,":[78],"we":[79],"propose":[80],"distribution-aware":[82],"approach,":[85],"called":[86],"CurveRL,":[87],"based":[88],"quantile":[91],"coordinate":[92],"transform,":[93],"which":[95],"weight":[97],"assigned":[98],"to":[99,117],"each":[100],"depends":[102],"not":[103],"absolute":[106],"value":[107],"pass":[109,124],"rates":[110,125],"but":[111],"its":[113],"rank":[114],"density":[116],"reflect":[118],"distributional":[120],"structure":[121],"learning":[128],"dynamics.":[129],"Extensive":[130],"experiments":[131],"across":[132],"multiple":[133],"benchmarks":[134],"demonstrate":[135],"our":[137],"proposed":[138],"CurveRL":[139],"consistently":[140],"outperforms":[141],"GRPO":[142],"other":[144],"RLVR":[145,161],"baselines.":[146],"Our":[147],"study":[148],"identifies":[149],"context-distribution":[150],"control":[151],"principled":[154],"axis":[155],"analyzing":[157],"designing":[159],"prompt-reweighted":[160],"algorithms.":[162],"The":[163],"code":[164],"is":[165],"released":[166],"https://github.com/zhyzmath/CurveRL.":[168]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-05-27T00:00:00"}