{"id":"https://openalex.org/W4412886997","doi":"https://doi.org/10.18653/v1/2025.acl-long.21","title":"Capture the Key in Reasoning to Enhance CoT Distillation Generalization","display_name":"Capture the Key in Reasoning to Enhance CoT Distillation Generalization","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4412886997","doi":"https://doi.org/10.18653/v1/2025.acl-long.21"},"language":"en","primary_location":{"id":"doi:10.18653/v1/2025.acl-long.21","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2025.acl-long.21","pdf_url":"https://aclanthology.org/2025.acl-long.21.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://aclanthology.org/2025.acl-long.21.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5108378458","display_name":"Chengwei Dai","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chengwei Dai","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100343513","display_name":"Ke Li","orcid":"https://orcid.org/0000-0002-7873-1554"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kun Li","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101866473","display_name":"Wei Zhou","orcid":"https://orcid.org/0000-0002-2548-6348"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wei Zhou","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5102820325","display_name":"Songlin Hu","orcid":"https://orcid.org/0000-0001-8559-1740"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Songlin Hu","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":true,"cited_by_count":1,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"441","last_page":"465"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.6237999796867371,"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/T10320","display_name":"Neural Networks and Applications","score":0.6237999796867371,"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/T12761","display_name":"Data Stream Mining Techniques","score":0.5681999921798706,"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/T11326","display_name":"Stock Market Forecasting Methods","score":0.5278000235557556,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.7859224677085876},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.7702105045318604},{"id":"https://openalex.org/keywords/distillation","display_name":"Distillation","score":0.7469964027404785},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6693643927574158},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.35038647055625916},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1144132912158966},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.10704740881919861},{"id":"https://openalex.org/keywords/chemistry","display_name":"Chemistry","score":0.09448269009590149},{"id":"https://openalex.org/keywords/chromatography","display_name":"Chromatography","score":0.09220710396766663}],"concepts":[{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.7859224677085876},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.7702105045318604},{"id":"https://openalex.org/C204030448","wikidata":"https://www.wikidata.org/wiki/Q101017","display_name":"Distillation","level":2,"score":0.7469964027404785},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6693643927574158},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.35038647055625916},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1144132912158966},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.10704740881919861},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.09448269009590149},{"id":"https://openalex.org/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"score":0.09220710396766663},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18653/v1/2025.acl-long.21","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2025.acl-long.21","pdf_url":"https://aclanthology.org/2025.acl-long.21.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.18653/v1/2025.acl-long.21","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2025.acl-long.21","pdf_url":"https://aclanthology.org/2025.acl-long.21.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)","raw_type":"proceedings-article"},"sustainable_development_goals":[{"display_name":"Zero hunger","score":0.49000000953674316,"id":"https://metadata.un.org/sdg/2"}],"awards":[{"id":"https://openalex.org/G5208670511","display_name":null,"funder_award_id":"U24A20335","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4412886997.pdf","grobid_xml":"https://content.openalex.org/works/W4412886997.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W3162204513","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890"],"abstract_inverted_index":{"As":[0],"Large":[1],"Language":[2,27],"Models":[3,28],"(LLMs)":[4],"scale":[5],"up":[6],"and":[7,85,183,191,201,245,291,330,396,443],"gain":[8],"powerful":[9],"Chain-of-Thoughts":[10],"(CoTs)":[11],"reasoning":[12,37,47,83,135,161,204],"abilities,":[13],"practical":[14],"resource":[15],"constraints":[16],"drive":[17],"efforts":[18],"to":[19,75,98,105,114,142,154,178,281,320,386,425],"distill":[20],"these":[21,93,180,188],"capabilities":[22],"into":[23],"more":[24],"compact":[25],"Smaller":[26],"(SLMs).We":[29],"find":[30],"that":[31,49,129,358],"CoTs":[32,65,157,176],"consist":[33],"mainly":[34],"of":[35,45,196,355,433,466],"simple":[36,140],"forms,":[38],"with":[39,159,311,347,416],"a":[40,126,431],"small":[41],"proportion":[42],"(":[43],"4.7%)":[44],"key":[46,121,134,181],"steps":[48,112,136,146,182],"truly":[50],"impact":[51],"conclusions.However,":[52],"previous":[53],"distillation":[54],"methods":[55],"typically":[56],"involve":[57],"supervised":[58],"fine-tuning":[59],"student":[60],"SLMs":[61,132],"only":[62,348],"on":[63,173,187,263,296,335,360,370,401,437,470],"correct":[64,106],"data":[66,158,177],"produced":[67],"by":[68],"teacher":[69],"LLMs,":[70],"resulting":[71],"in":[72,90,147],"students":[73],"struggling":[74],"learn":[76],"the":[77,81,110,144,168,174,185,194,211,223,252,256,297,302,306,316,336,341,349,353,361,365,374,402,407,411,421,438,451,455,459,464,471,476],"key,":[78],"instead":[79],"imitating":[80],"teacher's":[82],"forms":[84],"making":[86],"errors":[87],"or":[88,116],"omissions":[89],"reasoning.To":[91],"address":[92],"issues,":[94],"drawing":[95],"an":[96],"analogy":[97],"human":[99],"learning,":[100],"where":[101],"analyzing":[102],"mistakes":[103],"according":[104],"solutions":[107],"often":[108],"reveals":[109],"crucial":[111,145],"leading":[113],"successes":[115],"failures,":[117],"we":[118,149,166,299,308,338,344,404,413,448,457],"propose":[119],"mistakE-Driven":[120],"reasonIng":[122],"step":[123],"distillaTion":[124],"(EDIT),":[125],"novel":[127],"method":[128],"further":[130],"aids":[131],"learning":[133],"rather":[137],"than":[138],"mere":[139],"fine-tuning.Firstly,":[141],"expose":[143],"CoTs,":[148],"carefully":[150],"design":[151],"specific":[152],"prompts":[153],"generate":[155],"dual":[156,175],"similar":[160],"paths":[162],"but":[163],"divergent":[164],"conclusions.Then,":[165],"apply":[167],"minimum":[169],"edit":[170],"distance":[171],"algorithm":[172],"locate":[179],"optimize":[184],"likelihood":[186],"tokens.Extensive":[189],"experiments":[190],"analysis":[192],"validate":[193],"effectiveness":[195],"EDIT":[197],"across":[198],"both":[199],"in-domain(IND)":[200],"out-ofdomain(OOD)":[202],"benchmark":[203],"datasets":[205],"1":[206,214],".*":[207],"Kun":[208],"Li":[209],"is":[210,318,363,367,423,473,478],"corresponding":[212],"author.":[213],"Code":[215],"can":[216],"be":[217],"found":[218],"at":[219],"https://github.com/":[220],"C-W-D/EDIT":[221],"On":[222,373],"floor,":[224,257,307,375,412,456],"I":[225,249,376],"see":[226,377],"two":[227,242,246,271,287,326,378,392],"magenta":[228,247,253,288,303,327,342,379,393,408,452,461],"scrunchiephone":[229,240,260,289,294,314,328,333,351,356,380,394,399,419,435,446,462,467],"chargers,":[230,241,381],"one":[231,269,382],"gold":[232,236,383],"fidget":[233,384],"spinner,":[234],"three":[235,238,273,292,331,397],"booklets,":[237,244],"silver":[239,243,293,313,332,350,398,418,445],"booklets.If":[248],"remove":[250,300,339,405,449,458],"all":[251,301,340,406,450],"items":[254,304,409,453],"from":[255,305,410,454],"how":[258],"many":[259],"chargers":[261,290,295,329,334,357,395,400,436,442,468],"remain":[262,359],"it?Op":[264],"ons:":[265],"(A)":[266],"zero":[267],"(B)":[268],"(C)":[270],"(D)":[272],"(E)":[274],"four":[275],"(F)":[276],"five":[277],"(G)":[278],"six":[279],"According":[280],"this":[282,321,387,426],"ques":[283,322,388,427],"on,":[284,323,389,428],"there":[285,324,390,429],"are":[286,309,325,345,391,414,430],"floor.If":[298,337,403],"le":[310,346,415],"2":[312,417,440,460],"chargers.Therefore,":[315,352,420,463],"answer":[317,366,422,477],"(C).According":[319,424],"items,":[343],"number":[354,465],"floor":[362,472],"three.Therefore,":[364],"(D).Teacher":[368],"Ques":[369],"Unthinking":[371],"Student":[372],"spinner...According":[385],"total":[432],"5":[434],"floor:":[439],"magentascrunchiephone":[441],"3":[444],"chargers.If":[447],"remaining":[469],"3.":[474],"Therefore,":[475],"(D).":[479]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}