{"id":"https://openalex.org/W7164201778","doi":"https://doi.org/10.48550/arxiv.2606.09932","title":"When RL Fails after SFT: Rejuvenating Model Plasticity for Robust SFT-to-RL Handoff","display_name":"When RL Fails after SFT: Rejuvenating Model Plasticity for Robust SFT-to-RL Handoff","publication_year":2026,"publication_date":"2026-06-07","ids":{"openalex":"https://openalex.org/W7164201778","doi":"https://doi.org/10.48550/arxiv.2606.09932"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.09932","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.09932","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.2606.09932","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5138377842","display_name":"Runze Liu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Runze","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138294299","display_name":"Jiashun Liu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Jiashun","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138313555","display_name":"Xu Wan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wan, Xu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138383820","display_name":"Yuqian Fu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Fu, Yuqian","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5138336611","display_name":"Ling Pan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Pan, Ling","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":0.5073000192642212,"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":0.5073000192642212,"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":0.07119999825954437,"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/T13702","display_name":"Machine Learning in Healthcare","score":0.04560000076889992,"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":0.7021999955177307},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.6176000237464905},{"id":"https://openalex.org/keywords/security-token","display_name":"Security token","score":0.5895000100135803},{"id":"https://openalex.org/keywords/reset","display_name":"Reset (finance)","score":0.5196999907493591},{"id":"https://openalex.org/keywords/handover","display_name":"Handover","score":0.46950000524520874},{"id":"https://openalex.org/keywords/pipeline","display_name":"Pipeline (software)","score":0.44749999046325684},{"id":"https://openalex.org/keywords/simple","display_name":"Simple (philosophy)","score":0.3467000126838684}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7412999868392944},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.7021999955177307},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.6176000237464905},{"id":"https://openalex.org/C48145219","wikidata":"https://www.wikidata.org/wiki/Q1335365","display_name":"Security token","level":2,"score":0.5895000100135803},{"id":"https://openalex.org/C2779795794","wikidata":"https://www.wikidata.org/wiki/Q7315343","display_name":"Reset (finance)","level":2,"score":0.5196999907493591},{"id":"https://openalex.org/C111852164","wikidata":"https://www.wikidata.org/wiki/Q1414679","display_name":"Handover","level":2,"score":0.46950000524520874},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.44749999046325684},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3723999857902527},{"id":"https://openalex.org/C2780586882","wikidata":"https://www.wikidata.org/wiki/Q7520643","display_name":"Simple (philosophy)","level":2,"score":0.3467000126838684},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.30079999566078186},{"id":"https://openalex.org/C2777735758","wikidata":"https://www.wikidata.org/wiki/Q817765","display_name":"Path (computing)","level":2,"score":0.29899999499320984},{"id":"https://openalex.org/C79186407","wikidata":"https://www.wikidata.org/wiki/Q472074","display_name":"Plasticity","level":2,"score":0.27000001072883606},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.26820001006126404},{"id":"https://openalex.org/C45493050","wikidata":"https://www.wikidata.org/wiki/Q7884934","display_name":"Unified Model","level":2,"score":0.2667999863624573},{"id":"https://openalex.org/C28761237","wikidata":"https://www.wikidata.org/wiki/Q7805321","display_name":"Time horizon","level":2,"score":0.2538999915122986},{"id":"https://openalex.org/C177212765","wikidata":"https://www.wikidata.org/wiki/Q627335","display_name":"Workflow","level":2,"score":0.2529999911785126}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.09932","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.09932","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.2606.09932","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.09932","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":[{"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4","score":0.5980733036994934}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Supervised":[0],"Fine-Tuning":[1],"(SFT)":[2],"followed":[3],"by":[4,67],"Reinforcement":[5],"Learning":[6],"(RL)":[7],"has":[8],"become":[9],"a":[10,24,122,130],"standard":[11],"pipeline":[12],"for":[13,28],"Large":[14],"Language":[15],"Model":[16],"(LLM)":[17],"post-training.":[18],"SFT":[19,39,98,181],"is":[20],"expected":[21],"to":[22,30,50,63,100,114,148,157,187],"provide":[23],"useful":[25,140],"behavioral":[26],"prior":[27],"RL":[29,88,118,177],"further":[31],"enhance":[32],"model":[33,54,146,159],"capabilities.":[34],"However,":[35],"checkpoints":[36],"with":[37,153],"excessive":[38,97,150],"often":[40],"show":[41,93],"limited":[42],"improvement":[43],"during":[44],"RL.":[45,69],"We":[46],"attribute":[47],"this":[48,73],"failure":[49],"the":[51,56,117],"loss":[52],"of":[53,59],"plasticity:":[55],"reduced":[57],"ability":[58],"an":[60],"SFT-initialized":[61],"policy":[62],"be":[64],"effectively":[65],"reshaped":[66],"subsequent":[68],"To":[70,120],"better":[71],"understand":[72],"phenomenon,":[74],"we":[75,127],"conduct":[76],"detailed":[77],"analysis":[78],"from":[79,96],"multiple":[80],"perspectives,":[81],"including":[82],"parameter":[83,108],"changes,":[84],"output":[85],"spaces,":[86],"and":[87,105,168],"optimization":[89],"dynamics.":[90],"Our":[91],"results":[92,162],"that":[94,135,172],"models":[95],"tend":[99],"produce":[101],"over-confident":[102],"token":[103],"distributions":[104],"exhibit":[106],"sharp":[107],"landscapes,":[109],"which":[110],"make":[111],"them":[112],"harder":[113],"optimize":[115],"in":[116],"stage.":[119],"enable":[121],"more":[123],"robust":[124],"SFT-to-RL":[125],"handoff,":[126],"propose":[128],"\\texttt{Rejuvenation},":[129],"simple":[131],"yet":[132],"effective":[133],"method":[134],"restores":[136],"plasticity":[137],"while":[138,183],"preserving":[139],"SFT-acquired":[141],"priors.":[142],"Rejuvenation":[143],"leverages":[144],"base-anchored":[145],"fusion":[147],"reduce":[149],"SFT-induced":[151],"drift":[152],"targeted":[154],"neuron":[155],"reset":[156],"mitigate":[158],"rigidity.":[160],"Experimental":[161],"on":[163,179],"both":[164],"math":[165],"reasoning":[166],"tasks":[167,170],"agentic":[169],"demonstrate":[171],"our":[173],"approach":[174],"consistently":[175],"improves":[176],"performance":[178],"over-trained":[180],"models,":[182],"also":[184],"enhancing":[185],"generalization":[186],"out-of-distribution":[188],"tasks.":[189]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-06-11T00:00:00"}
