{"id":"https://openalex.org/W7160999494","doi":"https://doi.org/10.48550/arxiv.2605.11625","title":"Nice Fold or Hero Call: Learning Budget-Efficient Thinking for Adaptive Reasoning","display_name":"Nice Fold or Hero Call: Learning Budget-Efficient Thinking for Adaptive Reasoning","publication_year":2026,"publication_date":"2026-05-12","ids":{"openalex":"https://openalex.org/W7160999494","doi":"https://doi.org/10.48550/arxiv.2605.11625"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.11625","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.11625","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.2605.11625","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5136037825","display_name":"Zhaomeng Zhou","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhou, Zhaomeng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136023569","display_name":"Lan Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Lan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136083586","display_name":"Junyang Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Junyang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136066184","display_name":"Mu Yuan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yuan, Mu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5110593946","display_name":"Junda Lin","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lin, Junda","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/T11596","display_name":"Constraint Satisfaction and Optimization","score":0.211899995803833,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T11596","display_name":"Constraint Satisfaction and Optimization","score":0.211899995803833,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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":0.179299995303154,"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":0.06710000336170197,"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/logical-reasoning","display_name":"Logical reasoning","score":0.5559999942779541},{"id":"https://openalex.org/keywords/reasoning-system","display_name":"Reasoning system","score":0.5360000133514404},{"id":"https://openalex.org/keywords/case-based-reasoning","display_name":"Case-based reasoning","score":0.5228999853134155},{"id":"https://openalex.org/keywords/non-monotonic-logic","display_name":"Non-monotonic logic","score":0.5115000009536743},{"id":"https://openalex.org/keywords/deductive-reasoning","display_name":"Deductive reasoning","score":0.49869999289512634},{"id":"https://openalex.org/keywords/automated-reasoning","display_name":"Automated reasoning","score":0.47690001130104065},{"id":"https://openalex.org/keywords/adaptive-reasoning","display_name":"Adaptive reasoning","score":0.4526999890804291},{"id":"https://openalex.org/keywords/hero","display_name":"HERO","score":0.4309999942779541}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6363000273704529},{"id":"https://openalex.org/C43971567","wikidata":"https://www.wikidata.org/wiki/Q3142865","display_name":"Logical reasoning","level":2,"score":0.5559999942779541},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5436000227928162},{"id":"https://openalex.org/C89288958","wikidata":"https://www.wikidata.org/wiki/Q7301504","display_name":"Reasoning system","level":2,"score":0.5360000133514404},{"id":"https://openalex.org/C20162079","wikidata":"https://www.wikidata.org/wiki/Q1151406","display_name":"Case-based reasoning","level":2,"score":0.5228999853134155},{"id":"https://openalex.org/C159032336","wikidata":"https://www.wikidata.org/wiki/Q2488768","display_name":"Non-monotonic logic","level":2,"score":0.5115000009536743},{"id":"https://openalex.org/C97364631","wikidata":"https://www.wikidata.org/wiki/Q484284","display_name":"Deductive reasoning","level":2,"score":0.49869999289512634},{"id":"https://openalex.org/C195344581","wikidata":"https://www.wikidata.org/wiki/Q2555318","display_name":"Automated reasoning","level":2,"score":0.47690001130104065},{"id":"https://openalex.org/C107848011","wikidata":"https://www.wikidata.org/wiki/Q4680756","display_name":"Adaptive reasoning","level":4,"score":0.4526999890804291},{"id":"https://openalex.org/C51364203","wikidata":"https://www.wikidata.org/wiki/Q1563532","display_name":"HERO","level":2,"score":0.4309999942779541},{"id":"https://openalex.org/C86827895","wikidata":"https://www.wikidata.org/wiki/Q7098582","display_name":"Opportunistic reasoning","level":4,"score":0.4138999879360199},{"id":"https://openalex.org/C193221554","wikidata":"https://www.wikidata.org/wiki/Q5153664","display_name":"Commonsense reasoning","level":2,"score":0.4068000018596649},{"id":"https://openalex.org/C183521366","wikidata":"https://www.wikidata.org/wiki/Q7256422","display_name":"Psychology of reasoning","level":4,"score":0.3716000020503998},{"id":"https://openalex.org/C128913409","wikidata":"https://www.wikidata.org/wiki/Q3566063","display_name":"Belief revision","level":2,"score":0.3698999881744385},{"id":"https://openalex.org/C166088908","wikidata":"https://www.wikidata.org/wiki/Q308495","display_name":"Abductive reasoning","level":2,"score":0.35580000281333923},{"id":"https://openalex.org/C103057564","wikidata":"https://www.wikidata.org/wiki/Q4751139","display_name":"Analytic reasoning","level":3,"score":0.3483000099658966},{"id":"https://openalex.org/C37335422","wikidata":"https://www.wikidata.org/wiki/Q6888134","display_name":"Model-based reasoning","level":3,"score":0.31700000166893005},{"id":"https://openalex.org/C2779256446","wikidata":"https://www.wikidata.org/wiki/Q33959","display_name":"Nice","level":2,"score":0.31380000710487366},{"id":"https://openalex.org/C83725634","wikidata":"https://www.wikidata.org/wiki/Q7268699","display_name":"Qualitative reasoning","level":2,"score":0.3084000051021576},{"id":"https://openalex.org/C4554734","wikidata":"https://www.wikidata.org/wiki/Q593744","display_name":"Knowledge base","level":2,"score":0.3077000081539154},{"id":"https://openalex.org/C188147891","wikidata":"https://www.wikidata.org/wiki/Q147638","display_name":"Cognitive science","level":1,"score":0.2892000079154968},{"id":"https://openalex.org/C125014702","wikidata":"https://www.wikidata.org/wiki/Q4680749","display_name":"Adaptive learning","level":2,"score":0.2799000144004822},{"id":"https://openalex.org/C180747234","wikidata":"https://www.wikidata.org/wiki/Q23373","display_name":"Cognitive psychology","level":1,"score":0.2770000100135803},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.25529998540878296},{"id":"https://openalex.org/C161301231","wikidata":"https://www.wikidata.org/wiki/Q3478658","display_name":"Knowledge representation and reasoning","level":2,"score":0.2522999942302704}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.11625","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.11625","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.2605.11625","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.11625","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],"reasoning":[1,22,62,77,130,154,170,176],"models":[2],"(LRMs)":[3],"improve":[4],"problem":[5],"solving":[6],"through":[7],"extended":[8],"reasoning,":[9],"but":[10],"often":[11],"misallocate":[12],"test-time":[13],"compute.":[14],"Existing":[15],"efficiency":[16,179],"methods":[17],"reduce":[18],"cost":[19],"by":[20,156],"compressing":[21,49],"traces":[23],"or":[24],"conditioning":[25],"budget":[26,70],"on":[27,42,158],"perceived":[28,80],"difficulty,":[29],"yet":[30],"largely":[31],"overlook":[32],"solvability.":[33],"As":[34],"a":[35,64,92],"result,":[36],"they":[37],"may":[38],"spend":[39],"large":[40],"budgets":[41],"queries":[43,51,121],"beyond":[44],"the":[45,73],"model's":[46],"capability":[47],"while":[48,160],"hard-but-solvable":[50,143],"that":[52,95],"require":[53],"deeper":[54],"reasoning.":[55],"In":[56],"this":[57,85],"work,":[58],"we":[59,87],"formulate":[60],"adaptive":[61],"as":[63],"computational":[65],"investment":[66],"under":[67,101],"uncertainty,":[68],"where":[69],"should":[71],"follow":[72],"expected":[74,133],"return":[75],"of":[76],"rather":[78],"than":[79],"difficulty":[81],"alone.":[82],"To":[83],"instantiate":[84],"principle,":[86],"propose":[88],"Budget-Efficient":[89],"Thinking":[90],"(BET),":[91],"two-stage":[93],"framework":[94],"combines":[96],"behavioral":[97],"cold-start":[98],"with":[99,109,177],"GRPO":[100],"an":[102],"investment-cost-aware":[103],"reward.":[104],"By":[105],"aligning":[106],"solve-or-fold":[107],"decisions":[108],"rollout-derived":[110],"solvability,":[111],"BET":[112,152],"learns":[113],"three":[114,149],"behaviors:":[115],"(1)":[116],"short":[117],"solve,":[118],"answering":[119],"easy":[120],"concisely;":[122],"(2)":[123],"nice":[124],"fold,":[125],"abstaining":[126],"early":[127],"when":[128],"continued":[129],"has":[131],"near-zero":[132],"return;":[134],"and":[135,148,165,174],"(3)":[136],"hero":[137],"call,":[138],"preserving":[139],"sufficient":[140],"compute":[141],"for":[142],"queries.":[144],"Across":[145],"seven":[146],"benchmarks":[147],"base":[150],"models,":[151],"reduces":[153],"tokens":[155],"~55%":[157],"average":[159],"achieving":[161],"overall":[162],"performance":[163],"improvements,":[164],"transfers":[166],"zero-shot":[167],"from":[168],"mathematical":[169],"to":[171],"scientific":[172],"QA":[173],"logical":[175],"comparable":[178],"gains.":[180]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-05-14T00:00:00"}
