{"id":"https://openalex.org/W7127176924","doi":"https://doi.org/10.48550/arxiv.2601.23027","title":"Divide-and-Conquer CoT: RL for Reducing Latency via Parallel Reasoning","display_name":"Divide-and-Conquer CoT: RL for Reducing Latency via Parallel Reasoning","publication_year":2026,"publication_date":"2026-01-30","ids":{"openalex":"https://openalex.org/W7127176924","doi":"https://doi.org/10.48550/arxiv.2601.23027"},"language":null,"primary_location":{"id":"pmh:doi:10.48550/arxiv.2601.23027","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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},"type":"article","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/A5114637651","display_name":"Arvind Mahankali","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Mahankali, Arvind","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124807503","display_name":"Kaiyue Wen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wen, Kaiyue","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5124848685","display_name":"Tengyu Ma","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ma, Tengyu","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":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.12946895,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.2558000087738037,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.2558000087738037,"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/T10028","display_name":"Topic Modeling","score":0.17520000040531158,"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/T13523","display_name":"Mathematics, Computing, and Information Processing","score":0.04910000041127205,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/latency","display_name":"Latency (audio)","score":0.5817999839782715},{"id":"https://openalex.org/keywords/path","display_name":"Path (computing)","score":0.5228000283241272},{"id":"https://openalex.org/keywords/critical-path-method","display_name":"Critical path method","score":0.5185999870300293},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.4293000102043152},{"id":"https://openalex.org/keywords/base","display_name":"Base (topology)","score":0.35100001096725464},{"id":"https://openalex.org/keywords/measure","display_name":"Measure (data warehouse)","score":0.3425999879837036}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7748000025749207},{"id":"https://openalex.org/C82876162","wikidata":"https://www.wikidata.org/wiki/Q17096504","display_name":"Latency (audio)","level":2,"score":0.5817999839782715},{"id":"https://openalex.org/C2777735758","wikidata":"https://www.wikidata.org/wiki/Q817765","display_name":"Path (computing)","level":2,"score":0.5228000283241272},{"id":"https://openalex.org/C115874739","wikidata":"https://www.wikidata.org/wiki/Q825377","display_name":"Critical path method","level":2,"score":0.5185999870300293},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4293000102043152},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.40709999203681946},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3763999938964844},{"id":"https://openalex.org/C42058472","wikidata":"https://www.wikidata.org/wiki/Q810214","display_name":"Base (topology)","level":2,"score":0.35100001096725464},{"id":"https://openalex.org/C113775141","wikidata":"https://www.wikidata.org/wiki/Q428691","display_name":"Computer engineering","level":1,"score":0.3433000147342682},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.3425999879837036},{"id":"https://openalex.org/C46637626","wikidata":"https://www.wikidata.org/wiki/Q6693015","display_name":"Low latency (capital markets)","level":2,"score":0.33180001378059387},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.328000009059906},{"id":"https://openalex.org/C4554734","wikidata":"https://www.wikidata.org/wiki/Q593744","display_name":"Knowledge base","level":2,"score":0.31949999928474426},{"id":"https://openalex.org/C17458331","wikidata":"https://www.wikidata.org/wiki/Q935672","display_name":"Spawn (biology)","level":2,"score":0.30169999599456787},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2996000051498413},{"id":"https://openalex.org/C2989134064","wikidata":"https://www.wikidata.org/wiki/Q288510","display_name":"Execution time","level":2,"score":0.2924000024795532},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.28049999475479126},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.25060001015663147}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:doi:10.48550/arxiv.2601.23027","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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},{"id":"doi:10.48550/arxiv.2601.23027","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2601.23027","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":"Preprint"}],"best_oa_location":{"id":"pmh:doi:10.48550/arxiv.2601.23027","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":null,"license_id":null,"version":"submittedVersion","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":{"Long":[0],"chain-of-thought":[1],"reasoning":[2,61],"(Long":[3],"CoT)":[4],"is":[5,18,73,85],"now":[6],"fundamental":[7],"to":[8,25,31,36,67,74,115,119,143],"state-of-the-art":[9],"LLMs,":[10],"especially":[11],"in":[12,57,59,122],"mathematical":[13],"reasoning.":[14],"However,":[15],"LLM":[16],"generation":[17],"highly":[19],"sequential,":[20],"and":[21,63,105,159,179],"long":[22,100],"CoTs":[23],"lead":[24],"a":[26,47,79,86,99,110,123,134],"high":[27,76],"latency.":[28,39],"We":[29,96],"propose":[30],"train":[32],"Divide-and-Conquer":[33],"CoT":[34,101],"(DC-CoT)":[35],"reduce":[37],"the":[38,42,69,90,94,129,145,149],"With":[40],"DC-CoT,":[41],"model":[43,103],"can":[44,54],"act":[45],"as":[46,166],"director":[48],"that":[49,53],"identifies":[50],"distinct":[51],"subtasks":[52],"be":[55],"performed":[56],"parallel":[58],"its":[60,117],"process,":[62],"then":[64],"spawns":[65],"workers":[66,121],"execute":[68],"subtasks.":[70],"Our":[71,175],"goal":[72],"achieve":[75],"accuracy,":[77],"with":[78,98,109,138],"low":[80],"longest":[81,150,170],"path":[82,151,171],"length,":[83],"which":[84],"theoretical":[87],"measure":[88],"of":[89],"latency":[91],"needed":[92],"for":[93],"response.":[95],"start":[97],"base":[102],"(DeepScaleR-1.5B-Preview),":[104],"first":[106],"use":[107],"SFT":[108,127,177],"small":[111],"curated":[112],"demonstration":[113],"set":[114],"initialize":[116],"ability":[118],"spawn":[120],"certain":[124],"format.":[125],"Because":[126],"degrades":[128],"accuracy":[130,146,165],"significantly,":[131],"we":[132],"design":[133],"multi-stage":[135],"RL":[136],"algorithm,":[137],"various":[139],"data":[140],"filtering":[141],"strategies,":[142],"recover":[144],"while":[147,168],"decreasing":[148,169],"length.":[152],"Across":[153],"several":[154],"benchmarks":[155],"including":[156],"AIME":[157],"2024":[158],"HMMT":[160],"2025,":[161],"DC-CoT":[162],"achieves":[163],"similar":[164],"DeepScaleR-1.5B-Preview":[167],"length":[172],"by":[173],"35-40%.":[174],"code,":[176],"dataset":[178],"models":[180],"are":[181],"publicly":[182],"available":[183],"at":[184],"https://github.com/amahankali10/DC_CoT_RL_for_Low_Latency_CoT_with_Parallel_Reasoning.":[185]},"counts_by_year":[],"updated_date":"2026-07-15T18:14:33.161393","created_date":"2026-02-03T00:00:00"}