{"id":"https://openalex.org/W4412888256","doi":"https://doi.org/10.18653/v1/2025.findings-acl.520","title":"\u201cWell, Keep Thinking\u201d: Enhancing LLM Reasoning with Adaptive Injection Decoding","display_name":"\u201cWell, Keep Thinking\u201d: Enhancing LLM Reasoning with Adaptive Injection Decoding","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4412888256","doi":"https://doi.org/10.18653/v1/2025.findings-acl.520"},"language":"en","primary_location":{"id":"doi:10.18653/v1/2025.findings-acl.520","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2025.findings-acl.520","pdf_url":"https://aclanthology.org/2025.findings-acl.520.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 2025","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://aclanthology.org/2025.findings-acl.520.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5119181385","display_name":"Hyunbin Jin","orcid":null},"institutions":[{"id":"https://openalex.org/I139264467","display_name":"Seoul National University","ror":"https://ror.org/04h9pn542","country_code":"KR","type":"education","lineage":["https://openalex.org/I139264467"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Hyunbin Jin","raw_affiliation_strings":["Graduate School of Data Science , Seoul National University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Graduate School of Data Science , Seoul National University","institution_ids":["https://openalex.org/I139264467"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5119181386","display_name":"Je Won Yeom","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Je Won Yeom","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5119181387","display_name":"Seunghyun Bae","orcid":null},"institutions":[{"id":"https://openalex.org/I139264467","display_name":"Seoul National University","ror":"https://ror.org/04h9pn542","country_code":"KR","type":"education","lineage":["https://openalex.org/I139264467"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Seunghyun Bae","raw_affiliation_strings":["Graduate School of Data Science , Seoul National University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Graduate School of Data Science , Seoul National University","institution_ids":["https://openalex.org/I139264467"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5038795117","display_name":"Taesup Kim","orcid":null},"institutions":[{"id":"https://openalex.org/I139264467","display_name":"Seoul National University","ror":"https://ror.org/04h9pn542","country_code":"KR","type":"education","lineage":["https://openalex.org/I139264467"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Taesup Kim","raw_affiliation_strings":["Graduate School of Data Science , Seoul National University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Graduate School of Data Science , Seoul National University","institution_ids":["https://openalex.org/I139264467"]}]}],"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":0.08598861,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"9989","last_page":"10018"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10181","display_name":"Natural Language Processing Techniques","score":0.9635999798774719,"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/T10181","display_name":"Natural Language Processing Techniques","score":0.9635999798774719,"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":0.7089424133300781},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5753979086875916},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.0934106707572937}],"concepts":[{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.7089424133300781},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5753979086875916},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.0934106707572937}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18653/v1/2025.findings-acl.520","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2025.findings-acl.520","pdf_url":"https://aclanthology.org/2025.findings-acl.520.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 2025","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.18653/v1/2025.findings-acl.520","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2025.findings-acl.520","pdf_url":"https://aclanthology.org/2025.findings-acl.520.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 2025","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2045000886","display_name":null,"funder_award_id":"RS-2023-00222663","funder_id":"https://openalex.org/F4320322120","funder_display_name":"National Research Foundation of Korea"}],"funders":[{"id":"https://openalex.org/F4320320671","display_name":"National Research Foundation","ror":"https://ror.org/05s0g1g46"},{"id":"https://openalex.org/F4320322120","display_name":"National Research Foundation of Korea","ror":"https://ror.org/013aysd81"},{"id":"https://openalex.org/F4320328359","display_name":"Ministry of Science and ICT, South Korea","ror":"https://ror.org/01wpjm123"},{"id":"https://openalex.org/F4320335489","display_name":"Institute for Information and Communications Technology Promotion","ror":"https://ror.org/01g0hqq23"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4412888256.pdf","grobid_xml":"https://content.openalex.org/works/W4412888256.grobid-xml"},"referenced_works_count":1,"referenced_works":["https://openalex.org/W6602430550"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052"],"abstract_inverted_index":{"Large":[0],"language":[1],"models":[2],"(LLMs)":[3],"exhibit":[4],"strong":[5],"reasoning":[6,29,43,71,95,101,111],"abilities,":[7],"often":[8],"attributed":[9],"to":[10,65,88,122],"few-shot":[11],"or":[12,90],"zero-shot":[13,51],"Chain-of-Thought":[14],"(CoT)":[15],"prompting.While":[16],"effective,":[17],"these":[18],"methods":[19],"require":[20],"labor-intensive":[21],"prompt":[22],"engineering,":[23],"raising":[24],"the":[25,42,75,84,114],"question":[26],"of":[27,45,116],"whether":[28],"can":[30],"be":[31],"induced":[32],"without":[33,47],"reliance":[34],"on":[35,99],"explicit":[36,48],"prompts.In":[37],"this":[38],"work,":[39],"we":[40,55,73],"unlock":[41],"capabilities":[44],"LLMs":[46,64],"prompting.Inspired":[49],"by":[50],"CoT":[52],"and":[53,78],"CoT-decoding,":[54],"propose":[56],"a":[57,80],"novel":[58],"decoding":[59],"strategy":[60,107],"that":[61,104],"systematically":[62],"nudges":[63],"continue":[66],"reasoning,":[67],"thereby":[68],"preventing":[69],"immature":[70],"processes.Specifically,":[72],"monitor":[74],"model's":[76],"generation":[77],"inject":[79],"designated":[81],"phrase,":[82],"whenever":[83],"model":[85],"is":[86],"likely":[87],"halt":[89],"drift":[91],"away":[92],"from":[93],"logical":[94],"process.Our":[96],"experimental":[97],"evaluations":[98],"diverse":[100],"benchmarks":[102],"demonstrate":[103],"our":[105],"proposed":[106],"substantially":[108],"improves":[109],"LLM":[110],"capabilities,":[112],"highlighting":[113],"potential":[115],"decoding-based":[117],"interventions":[118],"as":[119],"an":[120],"alternative":[121],"traditional":[123],"prompting":[124],"techniques.":[125]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
