{"id":"https://openalex.org/W7128710297","doi":"https://doi.org/10.48550/arxiv.2602.11089","title":"DataChef: Cooking Up Optimal Data Recipes for LLM Adaptation via Reinforcement Learning","display_name":"DataChef: Cooking Up Optimal Data Recipes for LLM Adaptation via Reinforcement Learning","publication_year":2026,"publication_date":"2026-02-11","ids":{"openalex":"https://openalex.org/W7128710297","doi":"https://doi.org/10.48550/arxiv.2602.11089"},"language":null,"primary_location":{"id":"pmh:doi:10.48550/arxiv.2602.11089","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"publisher-specific-oa","license_id":"https://openalex.org/licenses/publisher-specific-oa","version":"submittedVersion","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":null,"any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5125733409","display_name":"Yicheng Chen","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Chen, Yicheng","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5109748044","display_name":"Zerun Ma","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ma, Zerun","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5125744015","display_name":"Xinchen Xie","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xie, Xinchen","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040395286","display_name":"Yining Li","orcid":"https://orcid.org/0000-0003-1753-0887"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Yining","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5125761240","display_name":"Kai Chen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Kai","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5125733409"],"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":0.31949999928474426,"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":0.31949999928474426,"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":0.15049999952316284,"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/T11636","display_name":"Artificial Intelligence in Healthcare and Education","score":0.08399999886751175,"subfield":{"id":"https://openalex.org/subfields/2718","display_name":"Health Informatics"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/recipe","display_name":"Recipe","score":0.82669997215271},{"id":"https://openalex.org/keywords/pipeline","display_name":"Pipeline (software)","score":0.5515999794006348},{"id":"https://openalex.org/keywords/raw-data","display_name":"Raw data","score":0.51910001039505},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.4925000071525574},{"id":"https://openalex.org/keywords/adaptation","display_name":"Adaptation (eye)","score":0.48429998755455017},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.4325999915599823},{"id":"https://openalex.org/keywords/bridge","display_name":"Bridge (graph theory)","score":0.4007999897003174},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.39899998903274536},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.39430001378059387}],"concepts":[{"id":"https://openalex.org/C2778671685","wikidata":"https://www.wikidata.org/wiki/Q219239","display_name":"Recipe","level":2,"score":0.82669997215271},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6345999836921692},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.5515999794006348},{"id":"https://openalex.org/C132964779","wikidata":"https://www.wikidata.org/wiki/Q2110223","display_name":"Raw data","level":2,"score":0.51910001039505},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5145000219345093},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.4925000071525574},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4876999855041504},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.48429998755455017},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.4325999915599823},{"id":"https://openalex.org/C100776233","wikidata":"https://www.wikidata.org/wiki/Q2532492","display_name":"Bridge (graph theory)","level":2,"score":0.4007999897003174},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.39899998903274536},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.39430001378059387},{"id":"https://openalex.org/C2776904630","wikidata":"https://www.wikidata.org/wiki/Q356336","display_name":"Adept","level":3,"score":0.35499998927116394},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.351500004529953},{"id":"https://openalex.org/C138827492","wikidata":"https://www.wikidata.org/wiki/Q6661985","display_name":"Data processing","level":2,"score":0.35030001401901245},{"id":"https://openalex.org/C133462117","wikidata":"https://www.wikidata.org/wiki/Q4929239","display_name":"Data collection","level":2,"score":0.3440000116825104},{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.32030001282691956},{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.303600013256073},{"id":"https://openalex.org/C127705205","wikidata":"https://www.wikidata.org/wiki/Q5748245","display_name":"Heuristics","level":2,"score":0.30059999227523804},{"id":"https://openalex.org/C121687571","wikidata":"https://www.wikidata.org/wiki/Q4677630","display_name":"Activity recognition","level":2,"score":0.28619998693466187},{"id":"https://openalex.org/C90673727","wikidata":"https://www.wikidata.org/wiki/Q901718","display_name":"Product (mathematics)","level":2,"score":0.28060001134872437},{"id":"https://openalex.org/C107524782","wikidata":"https://www.wikidata.org/wiki/Q40164","display_name":"Lever","level":2,"score":0.2741999924182892},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.2639000117778778},{"id":"https://openalex.org/C42058472","wikidata":"https://www.wikidata.org/wiki/Q810214","display_name":"Base (topology)","level":2,"score":0.2628999948501587},{"id":"https://openalex.org/C33762810","wikidata":"https://www.wikidata.org/wiki/Q461671","display_name":"Data integrity","level":2,"score":0.2621000111103058},{"id":"https://openalex.org/C18762648","wikidata":"https://www.wikidata.org/wiki/Q42213","display_name":"Work (physics)","level":2,"score":0.25540000200271606},{"id":"https://openalex.org/C4554734","wikidata":"https://www.wikidata.org/wiki/Q593744","display_name":"Knowledge base","level":2,"score":0.25220000743865967}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:doi:10.48550/arxiv.2602.11089","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"publisher-specific-oa","license_id":"https://openalex.org/licenses/publisher-specific-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},{"id":"doi:10.48550/arxiv.2602.11089","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2602.11089","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":"pmh:doi:10.48550/arxiv.2602.11089","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"publisher-specific-oa","license_id":"https://openalex.org/licenses/publisher-specific-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},"sustainable_development_goals":[{"display_name":"Decent work and economic growth","score":0.6467065811157227,"id":"https://metadata.un.org/sdg/8"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"In":[0],"the":[1,9,27,44,61,118,158,165,174],"current":[2],"landscape":[3],"of":[4,11,20,47,64,98],"Large":[5],"Language":[6],"Models":[7],"(LLMs),":[8],"curation":[10],"large-scale,":[12],"high-quality":[13],"training":[14,41,187],"data":[15,33,52,57,65,85,100,110],"is":[16,26,104],"a":[17,32,92,96,102,108,114,130],"primary":[18],"driver":[19],"model":[21,103],"performance.":[22],"A":[23],"key":[24],"lever":[25],"\\emph{data":[28],"recipe},":[29],"which":[30,124],"comprises":[31],"processing":[34,53],"pipeline":[35],"to":[36,49,106,117,151,164],"transform":[37],"raw":[38],"sources":[39],"into":[40],"corpora.":[42],"Despite":[43],"growing":[45],"use":[46],"LLMs":[48],"automate":[50],"individual":[51],"steps,":[54],"such":[55],"as":[56],"synthesis":[58],"and":[59,70,76,95,172,188],"filtering,":[60],"overall":[62],"design":[63],"recipes":[66,146],"remains":[67],"largely":[68],"manual":[69],"labor-intensive,":[71],"requiring":[72],"substantial":[73],"human":[74,155],"expertise":[75],"iteration.":[77],"To":[78],"bridge":[79],"this":[80],"gap,":[81],"we":[82],"formulate":[83],"\\emph{end-to-end":[84],"recipe":[86,111,159],"generation}":[87],"for":[88,137],"LLM":[89,116,186],"adaptation.":[90],"Given":[91],"target":[93,119],"benchmark":[94],"pool":[97],"available":[99],"sources,":[101],"required":[105],"output":[107],"complete":[109],"that":[112,133,147],"adapts":[113,162],"base":[115],"task.":[120],"We":[121],"present":[122],"DataChef-32B,":[123],"performs":[125],"online":[126],"reinforcement":[127],"learning":[128],"using":[129],"proxy":[131],"reward":[132],"predicts":[134],"downstream":[135],"performance":[136,149],"candidate":[138],"recipes.":[139],"Across":[140],"six":[141],"held-out":[142],"tasks,":[143],"DataChef-32B":[144,161],"produces":[145],"yield":[148],"comparable":[150],"those":[152],"curated":[153],"by":[154],"experts.":[156],"Notably,":[157],"from":[160],"Qwen3-1.7B-Base":[163],"math":[166],"domain,":[167],"achieving":[168],"66.7":[169],"on":[170,184],"AIME'25":[171],"surpassing":[173],"official":[175],"post-training":[176],"checkpoint":[177],"(Qwen3-1.7B).":[178],"This":[179],"work":[180],"sheds":[181],"new":[182],"light":[183],"automating":[185],"developing":[189],"self-evolving":[190],"AI":[191],"systems.":[192]},"counts_by_year":[],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2026-02-13T00:00:00"}