{"id":"https://openalex.org/W7166879176","doi":"https://doi.org/10.18653/v1/2026.findings-acl.33","title":"C3D: Enhancing LLM Reasoning via Confidence-Guided Contrastive Decoding","display_name":"C3D: Enhancing LLM Reasoning via Confidence-Guided Contrastive Decoding","publication_year":2026,"publication_date":"2026-01-01","ids":{"openalex":"https://openalex.org/W7166879176","doi":"https://doi.org/10.18653/v1/2026.findings-acl.33"},"language":null,"primary_location":{"id":"doi:10.18653/v1/2026.findings-acl.33","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2026.findings-acl.33","pdf_url":"https://aclanthology.org/2026.findings-acl.33.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":"Findings of the Association for Computational Linguistics: ACL 2026","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://aclanthology.org/2026.findings-acl.33.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5139826877","display_name":"Yufeng Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210100255","display_name":"Beijing Academy of Artificial Intelligence","ror":"https://ror.org/016a74861","country_code":"CN","type":"other","lineage":["https://openalex.org/I4210100255"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yufeng Zhang","raw_affiliation_strings":["Institute of Automation , Chinese Academy of Sciences","School of Artificial Intelligence , University of Chinese Academy of Sciences"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Automation , Chinese Academy of Sciences","institution_ids":["https://openalex.org/I19820366"]},{"raw_affiliation_string":"School of Artificial Intelligence , University of Chinese Academy of Sciences","institution_ids":["https://openalex.org/I4210100255"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101619658","display_name":"Xuepeng Wang","orcid":"https://orcid.org/0000-0002-6015-8139"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xuepeng Wang","raw_affiliation_strings":["Institute of Automation , Chinese Academy of Sciences","Wuhan AI Research"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Automation , Chinese Academy of Sciences","institution_ids":["https://openalex.org/I19820366"]},{"raw_affiliation_string":"Wuhan AI Research","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139718716","display_name":"Lingxiang Wu","orcid":null},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lingxiang Wu","raw_affiliation_strings":["Institute of Automation , Chinese Academy of Sciences","Wuhan AI Research"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Automation , Chinese Academy of Sciences","institution_ids":["https://openalex.org/I19820366"]},{"raw_affiliation_string":"Wuhan AI Research","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5139843334","display_name":"Jinqiao Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jinqiao Wang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"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":0.83647718,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"700","last_page":"712"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.21770000457763672,"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":0.21770000457763672,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.15710000693798065,"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/T11010","display_name":"Logic, Reasoning, and Knowledge","score":0.13369999825954437,"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/decoding-methods","display_name":"Decoding methods","score":0.4731999933719635},{"id":"https://openalex.org/keywords/encoding","display_name":"Encoding (memory)","score":0.3937000036239624},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.2782000005245209},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.2660999894142151},{"id":"https://openalex.org/keywords/scheme","display_name":"Scheme (mathematics)","score":0.26170000433921814}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6334999799728394},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5532000064849854},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.4731999933719635},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.4311999976634979},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.3937000036239624},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.2782000005245209},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.2660999894142151},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.26170000433921814},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.2556999921798706},{"id":"https://openalex.org/C20162079","wikidata":"https://www.wikidata.org/wiki/Q1151406","display_name":"Case-based reasoning","level":2,"score":0.2533999979496002}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18653/v1/2026.findings-acl.33","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2026.findings-acl.33","pdf_url":"https://aclanthology.org/2026.findings-acl.33.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":"Findings of the Association for Computational Linguistics: ACL 2026","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.18653/v1/2026.findings-acl.33","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2026.findings-acl.33","pdf_url":"https://aclanthology.org/2026.findings-acl.33.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":"Findings of the Association for Computational Linguistics: ACL 2026","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2899196128","display_name":null,"funder_award_id":"62276260","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":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7166879176.pdf","grobid_xml":"https://content.openalex.org/works/W7166879176.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Large":[0],"language":[1],"models":[2],"(LLMs)":[3],"are":[4],"prone":[5],"to":[6,38,46,69],"distraction":[7],"by":[8,30,78],"contextual":[9],"information":[10],"during":[11],"reasoning.Previous":[12],"work":[13],"primarily":[14],"focuses":[15],"on":[16],"improving":[17],"the":[18,21,26,48,52,64,70,76,80,83,92],"generation":[19],"of":[20,63,66,100],"next":[22],"token":[23],"while":[24],"overlooking":[25],"potential":[27],"bias":[28],"introduced":[29],"existing":[31],"premises.We":[32],"propose":[33],"a":[34,60],"novel":[35],"decoding":[36],"method":[37,88],"mitigate":[39],"such":[40],"biases.Our":[41],"framework":[42],"uses":[43],"predicted":[44],"logits":[45,81],"estimate":[47],"model's":[49],"confidence.By":[50],"decomposing":[51],"full":[53],"context":[54],"into":[55],"multiple":[56],"premises,":[57],"we":[58,74],"gain":[59],"clearer":[61],"understanding":[62],"relevance":[65],"each":[67,101],"premise":[68,102],"question.During":[71],"next-token":[72],"prediction,":[73],"refine":[75],"output":[77],"contrasting":[79],"with":[82],"highest":[84],"and":[85,96],"lowest":[86],"confidence.Our":[87],"effectively":[89],"reveals":[90],"how":[91],"model":[93],"dynamically":[94],"activates":[95],"adjusts":[97],"its":[98],"consideration":[99],"as":[103],"reasoning":[104],"progresses.":[105]},"counts_by_year":[],"updated_date":"2026-08-25T07:29:55.448023","created_date":"2026-07-02T00:00:00"}
