{"id":"https://openalex.org/W7131417431","doi":"https://doi.org/10.48550/arxiv.2602.19519","title":"Ada-RS: Adaptive Rejection Sampling for Selective Thinking","display_name":"Ada-RS: Adaptive Rejection Sampling for Selective Thinking","publication_year":2026,"publication_date":"2026-02-23","ids":{"openalex":"https://openalex.org/W7131417431","doi":"https://doi.org/10.48550/arxiv.2602.19519"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2602.19519","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2602.19519","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.2602.19519","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5126375953","display_name":"Yirou Ge","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Ge, Yirou","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5020534130","display_name":"Yixi Cai Lili lei Lei Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Yixi","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5126385450","display_name":"Alec Chiu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chiu, Alec","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5025142153","display_name":"Shivani Shekhar","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shekhar, Shivani","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5027581588","display_name":"Zijie Pan","orcid":"https://orcid.org/0000-0002-7644-1334"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Pan, Zijie","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5078222652","display_name":"Avinash Thangali","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Thangali, Avinash","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5126799945","display_name":"Yun-Shiuan Chuang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chuang, Yun-Shiuan","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5126791570","display_name":"Chaitanya Kulkarni","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kulkarni, Chaitanya","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5121545619","display_name":"Uma Kona","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kona, Uma","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033127375","display_name":"Linsey Pang","orcid":"https://orcid.org/0000-0002-4784-9795"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Pang, Linsey","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5126729350","display_name":"Prakhar Mehrotra","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Mehrotra, Prakhar","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":11,"corresponding_author_ids":["https://openalex.org/A5126375953"],"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":0.11299999803304672,"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":0.11299999803304672,"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/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.08309999853372574,"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/T11948","display_name":"Machine Learning in Materials Science","score":0.07010000199079514,"subfield":{"id":"https://openalex.org/subfields/2505","display_name":"Materials Chemistry"},"field":{"id":"https://openalex.org/fields/25","display_name":"Materials Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.5758000016212463},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.5551999807357788},{"id":"https://openalex.org/keywords/preference","display_name":"Preference","score":0.542900025844574},{"id":"https://openalex.org/keywords/sample","display_name":"Sample (material)","score":0.4426000118255615},{"id":"https://openalex.org/keywords/adaptive-sampling","display_name":"Adaptive sampling","score":0.41370001435279846},{"id":"https://openalex.org/keywords/lever","display_name":"Lever","score":0.4104999899864197},{"id":"https://openalex.org/keywords/simple","display_name":"Simple (philosophy)","score":0.38690000772476196}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6310999989509583},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.5758000016212463},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.5551999807357788},{"id":"https://openalex.org/C2781249084","wikidata":"https://www.wikidata.org/wiki/Q908656","display_name":"Preference","level":2,"score":0.542900025844574},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5148000121116638},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4790000021457672},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.4426000118255615},{"id":"https://openalex.org/C2781395549","wikidata":"https://www.wikidata.org/wiki/Q4680762","display_name":"Adaptive sampling","level":3,"score":0.41370001435279846},{"id":"https://openalex.org/C107524782","wikidata":"https://www.wikidata.org/wiki/Q40164","display_name":"Lever","level":2,"score":0.4104999899864197},{"id":"https://openalex.org/C2780586882","wikidata":"https://www.wikidata.org/wiki/Q7520643","display_name":"Simple (philosophy)","level":2,"score":0.38690000772476196},{"id":"https://openalex.org/C20353970","wikidata":"https://www.wikidata.org/wiki/Q1056998","display_name":"Simple random sample","level":3,"score":0.382099986076355},{"id":"https://openalex.org/C2984391234","wikidata":"https://www.wikidata.org/wiki/Q195771","display_name":"Sequential sampling","level":3,"score":0.3285999894142151},{"id":"https://openalex.org/C2982777018","wikidata":"https://www.wikidata.org/wiki/Q99268086","display_name":"Adaptive design","level":3,"score":0.3127000033855438},{"id":"https://openalex.org/C73602740","wikidata":"https://www.wikidata.org/wiki/Q7795822","display_name":"Thompson sampling","level":3,"score":0.2874000072479248},{"id":"https://openalex.org/C52740198","wikidata":"https://www.wikidata.org/wiki/Q1539564","display_name":"Importance sampling","level":3,"score":0.28299999237060547},{"id":"https://openalex.org/C2776207758","wikidata":"https://www.wikidata.org/wiki/Q5303302","display_name":"Downstream (manufacturing)","level":2,"score":0.2800000011920929},{"id":"https://openalex.org/C100776233","wikidata":"https://www.wikidata.org/wiki/Q2532492","display_name":"Bridge (graph theory)","level":2,"score":0.2538999915122986},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.25130000710487366}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2602.19519","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2602.19519","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.2602.19519","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2602.19519","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":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Large":[0],"language":[1],"models":[2],"(LLMs)":[3],"are":[4],"increasingly":[5],"being":[6],"deployed":[7],"in":[8,152],"cost":[9],"and":[10,31,45,124],"latency-sensitive":[11,153],"settings.":[12],"While":[13],"chain-of-thought":[14],"improves":[15,108],"reasoning,":[16],"it":[17],"can":[18],"waste":[19],"tokens":[20,119],"on":[21,100],"simple":[22],"requests.":[23],"We":[24,78],"study":[25],"selective":[26,44],"thinking":[27,126],"for":[28,42,75,149],"tool-using":[29],"LLMs":[30],"introduce":[32],"Adaptive":[33],"Rejection":[34],"Sampling":[35],"(Ada-RS),":[36],"an":[37,58],"algorithm-agnostic":[38],"sample":[39],"filtering":[40],"framework":[41],"learning":[43],"efficient":[46,150],"reasoning.":[47],"For":[48],"each":[49],"given":[50],"context,":[51],"Ada-RS":[52,81,107],"scores":[53],"multiple":[54],"sampled":[55],"completions":[56],"with":[57,98],"adaptive":[59],"length-penalized":[60],"reward":[61],"then":[62],"applies":[63],"stochastic":[64],"rejection":[65],"sampling":[66],"to":[67,122,130],"retain":[68],"only":[69],"high-reward":[70],"candidates":[71],"(or":[72],"preference":[73,85],"pairs)":[74],"downstream":[76],"optimization.":[77],"demonstrate":[79],"how":[80],"plugs":[82],"into":[83],"both":[84],"pair":[86],"(e.g.":[87,94],"DPO)":[88],"or":[89,134],"grouped":[90],"policy":[91],"optimization":[92],"strategies":[93],"DAPO).":[95],"Using":[96],"Qwen3-8B":[97],"LoRA":[99],"a":[101,146],"synthetic":[102],"tool":[103,136],"call-oriented":[104],"e-commerce":[105],"benchmark,":[106],"the":[109],"accuracy-efficiency":[110],"frontier":[111],"over":[112],"standard":[113],"algorithms":[114],"by":[115,120,128],"reducing":[116,125],"average":[117],"output":[118],"up":[121,129],"80%":[123],"rate":[127],"95%":[131],"while":[132],"maintaining":[133],"improving":[135],"call":[137],"accuracy.":[138],"These":[139],"results":[140],"highlight":[141],"that":[142],"training-signal":[143],"selection":[144],"is":[145],"powerful":[147],"lever":[148],"reasoning":[151],"deployments.":[154]},"counts_by_year":[],"updated_date":"2026-02-26T06:34:08.959763","created_date":"2026-02-26T00:00:00"}