{"id":"https://openalex.org/W7162656219","doi":"https://doi.org/10.48550/arxiv.2605.28791","title":"Skill-Conditioned Gated Self-Distillation for LLM Reasoning","display_name":"Skill-Conditioned Gated Self-Distillation for LLM Reasoning","publication_year":2026,"publication_date":"2026-05-27","ids":{"openalex":"https://openalex.org/W7162656219","doi":"https://doi.org/10.48550/arxiv.2605.28791"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.28791","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.28791","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.2605.28791","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101337138","display_name":"Jiazhen Huang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Huang, Jiazhen","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137195637","display_name":"Xiao Chen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Xiao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137247333","display_name":"Xiao Luo","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Luo, Xiao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137276799","display_name":"Yong Dai","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Dai, Yong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137236501","display_name":"Senkang Hu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hu, Senkang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5137264702","display_name":"Yuzhi Zhao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhao, Yuzhi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":6,"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":0.2957000136375427,"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":0.2957000136375427,"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/T11902","display_name":"Intelligent Tutoring Systems and Adaptive Learning","score":0.22910000383853912,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.08560000360012054,"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/code","display_name":"Code (set theory)","score":0.5291000008583069},{"id":"https://openalex.org/keywords/ask-price","display_name":"Ask price","score":0.4083999991416931},{"id":"https://openalex.org/keywords/non-monotonic-logic","display_name":"Non-monotonic logic","score":0.3465000092983246},{"id":"https://openalex.org/keywords/automated-reasoning","display_name":"Automated reasoning","score":0.3222000002861023},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.32179999351501465}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6251999735832214},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.5291000008583069},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.48539999127388},{"id":"https://openalex.org/C90329073","wikidata":"https://www.wikidata.org/wiki/Q914232","display_name":"Ask price","level":2,"score":0.4083999991416931},{"id":"https://openalex.org/C159032336","wikidata":"https://www.wikidata.org/wiki/Q2488768","display_name":"Non-monotonic logic","level":2,"score":0.3465000092983246},{"id":"https://openalex.org/C195344581","wikidata":"https://www.wikidata.org/wiki/Q2555318","display_name":"Automated reasoning","level":2,"score":0.3222000002861023},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.32179999351501465},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.31360000371932983},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.289900004863739},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.27410000562667847},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.27300000190734863},{"id":"https://openalex.org/C43126263","wikidata":"https://www.wikidata.org/wiki/Q128751","display_name":"Source code","level":2,"score":0.27250000834465027},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.26980000734329224},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.25429999828338623}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.28791","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.28791","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.2605.28791","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.28791","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/4","score":0.8339075446128845,"display_name":"Quality Education"}],"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],"self-distillation":[1],"(SD)":[2],"improves":[3,144],"LLM":[4],"reasoning":[5,138],"by":[6,165,169],"using":[7],"teacher-side":[8],"privileged":[9],"information":[10],"(PI)":[11],"to":[12],"turn":[13],"sparse":[14],"verifier":[15,98],"outcomes":[16],"into":[17],"dense":[18],"token-level":[19],"supervision.":[20],"Existing":[21],"methods":[22],"usually":[23],"assume":[24],"trusted":[25],"PI,":[26],"such":[27],"as":[28,70],"reference":[29],"answers":[30],"or":[31,58,106,131],"successful":[32],"traces.":[33],"We":[34,60],"ask":[35],"whether":[36],"PI":[37,156],"can":[38],"instead":[39],"come":[40],"from":[41],"an":[42],"experience-derived":[43],"skill":[44],"bank,":[45],"where":[46],"retrieved":[47],"skills":[48],"are":[49],"compact":[50],"and":[51,86,147,167,176],"reusable":[52],"but":[53],"may":[54],"also":[55],"be":[56],"irrelevant":[57],"misleading.":[59],"propose":[61],"Skill-Conditioned":[62],"Gated":[63],"Self-Distillation":[64],"(SGSD),":[65],"which":[66],"formulates":[67],"skill-based":[68],"SD":[69],"teacher":[71],"hypothesis":[72],"validation":[73],"rather":[74],"than":[75],"unconditional":[76],"imitation.":[77],"SGSD":[78,142,162],"retrieves":[79],"skill-mistake":[80],"pairs,":[81],"constructs":[82],"a":[83,104,108,154],"multi-teacher":[84],"pool,":[85],"lets":[87],"all":[88],"skill-conditioned":[89],"teachers":[90],"score":[91],"the":[92,114],"same":[93],"plain-prompt":[94],"student":[95],"rollout.":[96],"The":[97],"validates":[99],"each":[100],"teacher's":[101],"polarity:":[102],"supporting":[103],"success":[105],"suppressing":[107,129],"failure":[109],"gives":[110],"positive":[111],"supervision,":[112],"while":[113,128],"opposite":[115],"stance":[116],"is":[117,180],"reversed.":[118],"A":[119],"robust":[120],"gated":[121],"objective":[122],"then":[123],"distills":[124],"informative":[125],"teacher-student":[126],"disagreements":[127],"uncertain":[130],"extreme":[132],"signals.":[133],"Experiments":[134],"on":[135,160,171,173],"multiple":[136],"mathematical":[137],"benchmarks":[139],"show":[140],"that":[141],"consistently":[143],"over":[145],"GRPO":[146,164],"remains":[148],"competitive":[149],"with":[150],"answer-conditioned":[151],"OPSD":[152,168],"under":[153],"weaker":[155],"assumption.":[157],"For":[158],"example,":[159],"Qwen3-1.7B,":[161],"outperforms":[163],"6.2%":[166],"1.7%":[170],"average":[172],"AIME24,":[174],"AIME25,":[175],"HMMT25.":[177],"Our":[178],"code":[179],"available":[181],"at":[182],"https://github.com/walawalagoose/SGSD.":[183]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-05-29T00:00:00"}