{"id":"https://openalex.org/W7204945935","doi":"https://doi.org/10.18653/2026.emnlp-main.1119","title":"ERR+: Sequential Entropy Resolution for Efficient and Decisive LLM Reasoning","display_name":"ERR+: Sequential Entropy Resolution for Efficient and Decisive LLM Reasoning","publication_year":2026,"publication_date":"2026-01-01","ids":{"openalex":"https://openalex.org/W7204945935","doi":"https://doi.org/10.18653/2026.emnlp-main.1119"},"language":"en","primary_location":{"id":"doi:10.18653/2026.emnlp-main.1119","doi":"https://doi.org/10.18653/2026.emnlp-main.1119","is_oa":true,"landing_page_url":"https://doi.org/10.18653/2026.emnlp-main.1119","pdf_url":"https://aclanthology.org/2026.emnlp-main.1119.pdf","source":{"id":"https://openalex.org/S4363608991","display_name":"Conference on Empirical Methods in Natural Language Processing (EMNLP)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2026 Conference on Empirical Methods in Natural Language Processing","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","is_traditional":true,"indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"bronze","oa_url":"https://aclanthology.org/2026.emnlp-main.1119.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5139000809","display_name":"Xin Jiang","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I66867065","display_name":"East China Normal University","ror":"https://ror.org/02n96ep67","country_code":"CN","type":"education","lineage":["https://openalex.org/I66867065"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xin Jiang","raw_affiliation_strings":["School of Computer Science and Technology , East China Normal University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology , East China Normal University","institution_ids":["https://openalex.org/I66867065"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5032623222","display_name":"Minhao Wang","orcid":"https://orcid.org/0009-0004-0015-6643","observed_orcids":["https://orcid.org/0009-0004-0015-6643"]},"institutions":[{"id":"https://openalex.org/I66867065","display_name":"East China Normal University","ror":"https://ror.org/02n96ep67","country_code":"CN","type":"education","lineage":["https://openalex.org/I66867065"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Minhao Wang","raw_affiliation_strings":["School of Computer Science and Technology , East China Normal University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology , East China Normal University","institution_ids":["https://openalex.org/I66867065"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5125206305","display_name":"Wen Wu","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I4391768061","display_name":"State Key Laboratory of Estuarine and Coastal Research","ror":"https://ror.org/04d0j0m16","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4391768061","https://openalex.org/I66867065"]},{"id":"https://openalex.org/I66867065","display_name":"East China Normal University","ror":"https://ror.org/02n96ep67","country_code":"CN","type":"education","lineage":["https://openalex.org/I66867065"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wen Wu","raw_affiliation_strings":["State Key Laboratory of Estuarine and Coastal Research , School of Computer Science and Technology , East China Normal University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Estuarine and Coastal Research , School of Computer Science and Technology , East China Normal University","institution_ids":["https://openalex.org/I4391768061","https://openalex.org/I66867065"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5148871328","display_name":"Zhentao Xie","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I66867065","display_name":"East China Normal University","ror":"https://ror.org/02n96ep67","country_code":"CN","type":"education","lineage":["https://openalex.org/I66867065"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhentao Xie","raw_affiliation_strings":["School of Computer Science and Technology , East China Normal University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology , East China Normal University","institution_ids":["https://openalex.org/I66867065"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022828160","display_name":"Shangheng Du","orcid":"https://orcid.org/0000-0002-5792-631X","observed_orcids":["https://orcid.org/0000-0002-5792-631X"]},"institutions":[{"id":"https://openalex.org/I66867065","display_name":"East China Normal University","ror":"https://ror.org/02n96ep67","country_code":"CN","type":"education","lineage":["https://openalex.org/I66867065"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shangheng Du","raw_affiliation_strings":["School of Computer Science and Technology , East China Normal University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology , East China Normal University","institution_ids":["https://openalex.org/I66867065"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138552078","display_name":"Jinxin Shi","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I66867065","display_name":"East China Normal University","ror":"https://ror.org/02n96ep67","country_code":"CN","type":"education","lineage":["https://openalex.org/I66867065"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jinxin Shi","raw_affiliation_strings":["School of Computer Science and Technology , East China Normal University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology , East China Normal University","institution_ids":["https://openalex.org/I66867065"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100586328","display_name":"Jiabao Zhao","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I181326427","display_name":"Donghua University","ror":"https://ror.org/035psfh38","country_code":"CN","type":"education","lineage":["https://openalex.org/I181326427"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiabao Zhao","raw_affiliation_strings":["Donghua University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Donghua University","institution_ids":["https://openalex.org/I181326427"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5160144170","display_name":"Liang He","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I66867065","display_name":"East China Normal University","ror":"https://ror.org/02n96ep67","country_code":"CN","type":"education","lineage":["https://openalex.org/I66867065"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Liang He","raw_affiliation_strings":["School of Computer Science and Technology , East China Normal University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology , East China Normal University","institution_ids":["https://openalex.org/I66867065"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5160071941","display_name":"Weicong Chen","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I4405256866","display_name":"ByteDance (China)","ror":"https://ror.org/04m8av638","country_code":"CN","type":"company","lineage":["https://openalex.org/I4405256866"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weicong Chen","raw_affiliation_strings":["ByteDance"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"ByteDance","institution_ids":["https://openalex.org/I4405256866"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.0,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"25619","last_page":"25634"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.8798999786376953,"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":0.8798999786376953,"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":0.06729999929666519,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.013199999928474426,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/large-language-model-reasoning","display_name":"large language model reasoning","score":0.7770000100135803},{"id":"https://openalex.org/keywords/chain-of-thought","display_name":"chain-of-thought","score":0.722000002861023},{"id":"https://openalex.org/keywords/reinforcement-learning-with-verifiable-rewards","display_name":"reinforcement learning with verifiable rewards","score":0.9769999980926514},{"id":"https://openalex.org/keywords/uncertainty-resolution","display_name":"uncertainty resolution","score":0.5720000267028809},{"id":"https://openalex.org/keywords/gradient-conflict","display_name":"gradient conflict","score":0.6660000085830688}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6740999817848206},{"id":"https://openalex.org/C106301342","wikidata":"https://www.wikidata.org/wiki/Q4117933","display_name":"Entropy (arrow of time)","level":2,"score":0.5737000107765198},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4537999927997589},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.4440000057220459},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.41350001096725464},{"id":"https://openalex.org/C9679016","wikidata":"https://www.wikidata.org/wiki/Q1417473","display_name":"Principle of maximum entropy","level":2,"score":0.3443000018596649},{"id":"https://openalex.org/C2778994249","wikidata":"https://www.wikidata.org/wiki/Q2842324","display_name":"TRAC","level":2,"score":0.31929999589920044},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.3158999979496002},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.3001999855041504},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.29910001158714294},{"id":"https://openalex.org/C138268822","wikidata":"https://www.wikidata.org/wiki/Q1051925","display_name":"Resolution (logic)","level":2,"score":0.2937000095844269},{"id":"https://openalex.org/C171752962","wikidata":"https://www.wikidata.org/wiki/Q255166","display_name":"Kullback\u2013Leibler divergence","level":2,"score":0.288100004196167},{"id":"https://openalex.org/C120936955","wikidata":"https://www.wikidata.org/wiki/Q2155640","display_name":"Empirical research","level":2,"score":0.2791999876499176},{"id":"https://openalex.org/C85847156","wikidata":"https://www.wikidata.org/wiki/Q59015987","display_name":"Verifiable secret sharing","level":3,"score":0.2759999930858612},{"id":"https://openalex.org/C179518139","wikidata":"https://www.wikidata.org/wiki/Q5140297","display_name":"Coding (social sciences)","level":2,"score":0.26109999418258667}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.18653/2026.emnlp-main.1119","doi":"https://doi.org/10.18653/2026.emnlp-main.1119","is_oa":true,"landing_page_url":"https://doi.org/10.18653/2026.emnlp-main.1119","pdf_url":"https://aclanthology.org/2026.emnlp-main.1119.pdf","source":{"id":"https://openalex.org/S4363608991","display_name":"Conference on Empirical Methods in Natural Language Processing (EMNLP)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2026 Conference on Empirical Methods in Natural Language Processing","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2608.28771","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2608.28771","pdf_url":"https://arxiv.org/pdf/2608.28771","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2608.28771","doi":"https://doi.org/10.48550/arxiv.2608.28771","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2608.28771","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":false,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.18653/2026.emnlp-main.1119","doi":"https://doi.org/10.18653/2026.emnlp-main.1119","is_oa":true,"landing_page_url":"https://doi.org/10.18653/2026.emnlp-main.1119","pdf_url":"https://aclanthology.org/2026.emnlp-main.1119.pdf","source":{"id":"https://openalex.org/S4363608991","display_name":"Conference on Empirical Methods in Natural Language Processing (EMNLP)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2026 Conference on Empirical Methods in Natural Language Processing","raw_type":"proceedings-article"},"sustainable_development_goals":[],"study_designs":[],"awards":[{"id":"https://openalex.org/G6451395234","display_name":null,"funder_award_id":"62377013","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7177146160","display_name":null,"funder_award_id":"62477011","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"},{"id":"https://openalex.org/F4320329860","display_name":"National Science and Technology Major Project","ror":null},{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7204945935.pdf","grobid_xml":"https://content.openalex.org/works/W7204945935.grobid-xml"},"referenced_works_count":13,"referenced_works":["https://openalex.org/W4403746689","https://openalex.org/W4406774573","https://openalex.org/W4409049124","https://openalex.org/W4414281281","https://openalex.org/W4414939355","https://openalex.org/W4415318644","https://openalex.org/W4416048648","https://openalex.org/W4416118517","https://openalex.org/W4417539710","https://openalex.org/W6929328961","https://openalex.org/W6948351674","https://openalex.org/W7138345725","https://openalex.org/W7196953391"],"related_works":["https://openalex.org/W4416236317","https://openalex.org/W7152933809","https://openalex.org/W4415318644","https://openalex.org/W7131869551","https://openalex.org/W4417086737","https://openalex.org/W4414898977","https://openalex.org/W4416383319","https://openalex.org/W4416956409","https://openalex.org/W4414756195","https://openalex.org/W7134824536"],"abstract_inverted_index":{"Large":[0],"reasoning":[1,42,48,64],"models":[2],"achieve":[3],"strong":[4,27],"performance":[5],"on":[6,37,179],"complex":[7],"tasks":[8],"by":[9,114],"generating":[10],"extended":[11],"chain-of-thought":[12],"(CoT)":[13],"traces":[14],"via":[15,150],"reinforcement":[16],"learning":[17],"with":[18,29,95],"verifiable":[19],"rewards":[20,123],"(RLVR).While":[21],"current":[22],"RLVR":[23,86],"methods":[24,118],"have":[25],"achieved":[26],"results":[28],"correctness-based":[30],"reward":[31],"signals,":[32],"they":[33],"provide":[34,155],"limited":[35],"guidance":[36],"the":[38,41,46,76,96,110,124,137,164,174],"quality":[39],"of":[40,126,163],"process":[43],"itself,":[44],"leaving":[45,129],"internal":[47],"structure":[49],"largely":[50],"unoptimized.Through":[51],"empirical":[52],"analysis":[53,158],"across":[54,191],"multiple":[55],"model":[56,192],"families,":[57],"we":[58],"identify":[59],"a":[60,84,101,151,156],"consistent":[61,183],"pattern:":[62],"correct":[63],"trac":[65],"es":[66],"exhibit":[67],"more":[68],"frequent":[69],"and":[70,188],"larger":[71],"token-level":[72,106],"entropy":[73,107],"drops":[74,108],"within":[75],"thinking":[77,111],"phase":[78,93,135],"than":[79],"incorrect":[80],"ones.We":[81],"propose":[82],"ERR+,":[83],"two-phase":[85],"framework":[87],"grounded":[88],"in":[89,109,170,185],"this":[90],"observation.The":[91],"first":[92],"trains":[94],"Entropy":[97],"Relief":[98],"Reward":[99],"(ERR),":[100],"bonus":[102],"proportional":[103],"to":[104],"cumulative":[105],"phase,":[112],"log-normalized":[113],"response":[115,189],"length.Unlike":[116],"prior":[117],"that":[119,160],"suppress":[120],"entropy,":[121],"ERR":[122],"resolution":[125],"uncertainty":[127],"while":[128],"exploratory":[130],"high-entropy":[131],"states":[132],"unconstrained.The":[133],"second":[134],"introduces":[136],"Robust":[138],"Relative":[139],"Efficiency":[140],"Reward,":[141],"which":[142],"scores":[143],"each":[144],"response's":[145],"length":[146],"against":[147],"cogenerated":[148],"peers":[149],"tanh-transformed":[152],"withingroup":[153],"z-score.We":[154],"formal":[157],"showing":[159],"joint":[161],"optimization":[162],"two":[165],"objectives":[166],"induces":[167],"gradient":[168],"conflict":[169],"early":[171],"training,":[172],"motivating":[173],"sequential":[175],"design":[176],"(Theorem":[177],"1).Experiments":[178],"five":[180],"datasets":[181],"demonstrate":[182],"improvements":[184],"both":[186],"accuracy":[187],"conciseness":[190],"backbones.Our":[193],"code":[194],"is":[195],"available":[196],"at":[197],"https:":[198],"//github.com/XrkArul/err_response.":[199]},"counts_by_year":[],"updated_date":"2026-11-08T12:12:28.789561","created_date":"2026-09-02T00:00:00"}