{"id":"https://openalex.org/W7165675805","doi":"https://doi.org/10.48550/arxiv.2606.22942","title":"Understanding Knowledge Distillation in Post-Training: When It Helps and When It Fails","display_name":"Understanding Knowledge Distillation in Post-Training: When It Helps and When It Fails","publication_year":2026,"publication_date":"2026-06-22","ids":{"openalex":"https://openalex.org/W7165675805","doi":"https://doi.org/10.48550/arxiv.2606.22942"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.22942","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.22942","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":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2606.22942","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5139161727","display_name":"Xin Liu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Xin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014697788","display_name":"Simin Ma","orcid":"https://orcid.org/0000-0002-4906-3278"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ma, Simin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103870133","display_name":"Liu S","orcid":"https://orcid.org/0000-0001-7255-0982"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Shujian","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139169850","display_name":"Song Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Song","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139137799","display_name":"Sathish Reddy Indurthi","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Indurthi, Sathish Reddy","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139153942","display_name":"Haoyun Deng","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Deng, Haoyun","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139209513","display_name":"Lu Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Lu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5139146091","display_name":"Kaiqiang Song","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Song, Kaiqiang","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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.1834000051021576,"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"}},"topics":[{"id":"https://openalex.org/T11714","display_name":"Multimodal Machine Learning Applications","score":0.1834000051021576,"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/T10028","display_name":"Topic Modeling","score":0.13330000638961792,"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":0.0877000018954277,"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/software-deployment","display_name":"Software deployment","score":0.586899995803833},{"id":"https://openalex.org/keywords/distillation","display_name":"Distillation","score":0.5692999958992004},{"id":"https://openalex.org/keywords/work","display_name":"Work (physics)","score":0.4916999936103821},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.47530001401901245},{"id":"https://openalex.org/keywords/training","display_name":"Training (meteorology)","score":0.4171000123023987},{"id":"https://openalex.org/keywords/baseline","display_name":"Baseline (sea)","score":0.37310001254081726}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6847000122070312},{"id":"https://openalex.org/C105339364","wikidata":"https://www.wikidata.org/wiki/Q2297740","display_name":"Software deployment","level":2,"score":0.586899995803833},{"id":"https://openalex.org/C204030448","wikidata":"https://www.wikidata.org/wiki/Q101017","display_name":"Distillation","level":2,"score":0.5692999958992004},{"id":"https://openalex.org/C18762648","wikidata":"https://www.wikidata.org/wiki/Q42213","display_name":"Work (physics)","level":2,"score":0.4916999936103821},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4771000146865845},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.47530001401901245},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4571000039577484},{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.4171000123023987},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.37310001254081726},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.37040001153945923},{"id":"https://openalex.org/C182306322","wikidata":"https://www.wikidata.org/wiki/Q1779371","display_name":"Order (exchange)","level":2,"score":0.3140000104904175},{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.28040000796318054},{"id":"https://openalex.org/C2986750623","wikidata":"https://www.wikidata.org/wiki/Q830170","display_name":"Knowledge creation","level":3,"score":0.2702000141143799},{"id":"https://openalex.org/C56739046","wikidata":"https://www.wikidata.org/wiki/Q192060","display_name":"Knowledge management","level":1,"score":0.2671999931335449}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.22942","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.22942","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":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2606.22942","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.22942","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":"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":{"Large":[0],"language":[1],"models":[2,60,173],"(LLMs)":[3],"achieve":[4],"strong":[5],"performance":[6],"across":[7],"many":[8],"tasks,":[9],"but":[10,94],"their":[11],"high":[12],"computational":[13],"cost":[14],"limits":[15],"deployment":[16],"in":[17,75,91,174],"resource-constrained":[18],"environments.":[19,176],"Knowledge":[20],"Distillation":[21],"(KD)":[22],"offers":[23],"a":[24,31,35,39,70,106,146],"practical":[25,168],"solution":[26],"by":[27,156],"transferring":[28],"knowledge":[29,126],"from":[30,105,133],"teacher":[32,109,124],"model":[33],"of":[34,73],"larger":[36],"size":[37],"to":[38],"smaller":[40],"student":[41,129,165],"model.":[42],"While":[43],"prior":[44],"work":[45],"has":[46,61],"mainly":[47],"examined":[48],"task-specific":[49],"or":[50],"small-scale":[51],"settings,":[52],"the":[53,78,123,128,134],"post-training":[54,76],"stage":[55],"for":[56,170],"building":[57,171],"general":[58],"instruction-following":[59],"received":[62],"limited":[63],"attention.":[64],"In":[65],"this":[66],"paper,":[67],"we":[68],"conduct":[69],"systematic":[71],"study":[72,140],"KD":[74,86,119,148],"using":[77],"large-scale":[79],"Tulu":[80],"3":[81],"dataset.":[82],"We":[83,138],"find":[84],"that":[85,118,127,150],"outperforms":[87],"supervised":[88],"fine-tuning":[89],"(SFT)":[90],"low-data":[92],"regimes,":[93],"its":[95],"advantage":[96],"diminishes":[97],"as":[98],"more":[99],"training":[100,135],"data":[101,136,154],"is":[102],"added.":[103],"Distilling":[104],"stronger":[107],"instruction-tuned":[108],"restores":[110],"substantial":[111],"gains":[112],"even":[113],"with":[114],"abundant":[115],"data,":[116],"indicating":[117],"remains":[120],"effective":[121],"when":[122],"provides":[125],"cannot":[130],"easily":[131],"acquire":[132],"alone.":[137],"further":[139],"domain-specific,":[141],"low-resource":[142],"scenarios":[143],"and":[144],"propose":[145],"two-stage":[147],"strategy":[149],"leverages":[151],"synthetic":[152],"teacher-labeled":[153],"followed":[155],"refinement":[157],"on":[158],"human":[159],"annotations.":[160],"This":[161],"method":[162],"consistently":[163],"improves":[164],"performance,":[166],"providing":[167],"guidance":[169],"compact":[172],"data-scarce":[175]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-06-24T00:00:00"}
