{"id":"https://openalex.org/W7141388625","doi":"https://doi.org/10.48550/arxiv.2603.25562","title":"Revisiting On-Policy Distillation: Empirical Failure Modes and Simple Fixes","display_name":"Revisiting On-Policy Distillation: Empirical Failure Modes and Simple Fixes","publication_year":2026,"publication_date":"2026-03-26","ids":{"openalex":"https://openalex.org/W7141388625","doi":"https://doi.org/10.48550/arxiv.2603.25562"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.25562","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.25562","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":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2603.25562","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5130794549","display_name":"Yuqian Fu","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Fu, Yuqian","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130817390","display_name":"Haohuan Huang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Huang, Haohuan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073551629","display_name":"Kaiwen Jiang","orcid":"https://orcid.org/0000-0003-4837-2084"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jiang, Kaiwen","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5080193690","display_name":"Yuanheng Zhu","orcid":"https://orcid.org/0000-0001-5384-423X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Jiacai","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130816911","display_name":"Dongbin Zhao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jiang, Zhuo","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Zhu, Yuanheng","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhu, Yuanheng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":null,"display_name":"Zhao, Dongbin","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhao, Dongbin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5130794549"],"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":0.364300012588501,"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":0.364300012588501,"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/T10181","display_name":"Natural Language Processing Techniques","score":0.08410000056028366,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.06040000170469284,"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/variance","display_name":"Variance (accounting)","score":0.6890000104904175},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.5986999869346619},{"id":"https://openalex.org/keywords/estimator","display_name":"Estimator","score":0.5814999938011169},{"id":"https://openalex.org/keywords/simple","display_name":"Simple (philosophy)","score":0.5309000015258789},{"id":"https://openalex.org/keywords/coupling","display_name":"Coupling (piping)","score":0.4975999891757965},{"id":"https://openalex.org/keywords/signal","display_name":"SIGNAL (programming language)","score":0.4668999910354614},{"id":"https://openalex.org/keywords/sample","display_name":"Sample (material)","score":0.46160000562667847},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.4575999975204468}],"concepts":[{"id":"https://openalex.org/C196083921","wikidata":"https://www.wikidata.org/wiki/Q7915758","display_name":"Variance (accounting)","level":2,"score":0.6890000104904175},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6019999980926514},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.5986999869346619},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.5814999938011169},{"id":"https://openalex.org/C2780586882","wikidata":"https://www.wikidata.org/wiki/Q7520643","display_name":"Simple (philosophy)","level":2,"score":0.5309000015258789},{"id":"https://openalex.org/C131584629","wikidata":"https://www.wikidata.org/wiki/Q4308705","display_name":"Coupling (piping)","level":2,"score":0.4975999891757965},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.4668999910354614},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.46160000562667847},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.4575999975204468},{"id":"https://openalex.org/C52740198","wikidata":"https://www.wikidata.org/wiki/Q1539564","display_name":"Importance sampling","level":3,"score":0.3970000147819519},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.3898000121116638},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.37209999561309814},{"id":"https://openalex.org/C112972136","wikidata":"https://www.wikidata.org/wiki/Q7595718","display_name":"Stability (learning theory)","level":2,"score":0.33489999175071716},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3188999891281128},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3070000112056732},{"id":"https://openalex.org/C183115368","wikidata":"https://www.wikidata.org/wiki/Q856577","display_name":"Weighting","level":2,"score":0.30480000376701355},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.29980000853538513},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.29339998960494995},{"id":"https://openalex.org/C138268822","wikidata":"https://www.wikidata.org/wiki/Q1051925","display_name":"Resolution (logic)","level":2,"score":0.2759999930858612},{"id":"https://openalex.org/C75917345","wikidata":"https://www.wikidata.org/wiki/Q2725298","display_name":"Sampling bias","level":3,"score":0.2694000005722046},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.2671999931335449},{"id":"https://openalex.org/C110121322","wikidata":"https://www.wikidata.org/wiki/Q865811","display_name":"Distribution (mathematics)","level":2,"score":0.2662000060081482},{"id":"https://openalex.org/C121864883","wikidata":"https://www.wikidata.org/wiki/Q677916","display_name":"Statistical physics","level":1,"score":0.2632000148296356},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.2535000145435333},{"id":"https://openalex.org/C47446073","wikidata":"https://www.wikidata.org/wiki/Q5165890","display_name":"Control theory (sociology)","level":3,"score":0.2531999945640564},{"id":"https://openalex.org/C120936955","wikidata":"https://www.wikidata.org/wiki/Q2155640","display_name":"Empirical research","level":2,"score":0.251800000667572}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.25562","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.25562","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":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2603.25562","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.25562","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":"article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education","score":0.5215900540351868}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"On-policy":[0],"distillation":[1],"(OPD)":[2],"is":[3,67],"increasingly":[4],"used":[5],"in":[6],"LLM":[7],"post-training":[8],"because":[9],"it":[10],"can":[11,36],"leverage":[12],"a":[13,32,76,82,129,140,173,183],"teacher":[14,111,124,135],"model":[15],"to":[16,31,70],"provide":[17],"dense":[18],"supervision":[19],"on":[20,42,113],"student":[21,137],"rollouts.":[22],"The":[23],"standard":[24,178],"implementation,":[25],"however,":[26],"usually":[27],"reduces":[28],"distribution":[29],"matching":[30],"sampled-token":[33,105,179],"log-ratio,":[34],"which":[35],"make":[37],"the":[38,50],"learning":[39],"signal":[40],"fragile":[41],"long":[43],"rollouts":[44],"whose":[45],"prefixes":[46],"drift":[47],"away":[48],"from":[49,58],"teacher's":[51],"typical":[52],"support.":[53],"We":[54],"revisit":[55],"this":[56,166],"formulation":[57],"both":[59],"theoretical":[60],"and":[61,95,116,136,152,158,163,171],"implementation":[62],"perspectives.":[63],"Theoretically,":[64],"token-level":[65,108],"OPD":[66,180],"biased":[68],"relative":[69],"sequence-level":[71],"reverse-KL":[72,131],"minimization,":[73],"but":[74],"admits":[75],"substantially":[77],"tighter":[78],"worst-case":[79],"variance":[80,94],"bound;":[81],"controlled":[83],"synthetic":[84],"study":[85],"further":[86],"shows":[87],"that":[88,133],"stronger":[89],"future-reward":[90],"coupling":[91],"increases":[92],"gradient":[93],"destabilizes":[96],"training.":[97],"Empirically,":[98],"we":[99],"identify":[100],"three":[101],"failure":[102],"modes":[103],"of":[104],"OPD:":[106],"imbalanced":[107],"supervision,":[109],"unreliable":[110],"guidance":[112],"student-generated":[114],"prefixes,":[115],"tokenizer":[117],"or":[118],"special-token":[119,153],"mismatch.":[120],"These":[121],"findings":[122],"motivate":[123],"top-K":[125],"local":[126],"support":[127],"matching,":[128],"truncated":[130],"objective":[132,167],"compares":[134],"distributions":[138],"over":[139,177],"teacher-supported":[141],"token":[142],"set":[143],"at":[144],"each":[145],"prefix,":[146],"together":[147],"with":[148],"top-p":[149],"rollout":[150],"sampling":[151],"masking.":[154],"Across":[155],"single-task":[156],"reasoning":[157,164],"multi-task":[159],"benchmarks":[160],"spanning":[161],"agentic":[162],"settings,":[165],"improves":[168],"optimization":[169],"stability":[170],"yields":[172],"+19.8%":[174],"performance":[175],"gain":[176],"baselines,":[181],"providing":[182],"practical":[184],"recipe":[185],"for":[186],"more":[187],"stable":[188],"on-policy":[189],"distillation.":[190]},"counts_by_year":[],"updated_date":"2026-04-29T06:10:49.150238","created_date":"2026-03-28T00:00:00"}