{"id":"https://openalex.org/W4416035175","doi":"https://doi.org/10.18653/v1/2025.findings-emnlp.170","title":"Chain-of-Thought Matters: Improving Long-Context Language Models with Reasoning Path Supervision","display_name":"Chain-of-Thought Matters: Improving Long-Context Language Models with Reasoning Path Supervision","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4416035175","doi":"https://doi.org/10.18653/v1/2025.findings-emnlp.170"},"language":null,"primary_location":{"id":"doi:10.18653/v1/2025.findings-emnlp.170","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2025.findings-emnlp.170","pdf_url":"https://aclanthology.org/2025.findings-emnlp.170.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: EMNLP 2025","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://aclanthology.org/2025.findings-emnlp.170.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5077693662","display_name":"Dawei Zhu","orcid":"https://orcid.org/0000-0003-0167-6603"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Dawei Zhu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Xiyu Wei","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xiyu Wei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5080990023","display_name":"Gang Zhao","orcid":"https://orcid.org/0000-0001-8584-9510"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Guangxiang Zhao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057103339","display_name":"Wenhao Wu","orcid":"https://orcid.org/0000-0002-6350-3874"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wenhao Wu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101424425","display_name":"Hejian Zou","orcid":"https://orcid.org/0000-0002-2306-9778"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Haosheng Zou","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Junfeng Ran","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Junfeng Ran","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5120308779","display_name":"XWang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"XWang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037670975","display_name":"Lin Sun","orcid":"https://orcid.org/0000-0002-8781-2057"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lin Sun","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5005282757","display_name":"Xiangzheng Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xiangzheng Zhang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5058353424","display_name":"Sujian Li","orcid":"https://orcid.org/0000-0001-7493-0786"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sujian Li","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":2,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"3197","last_page":"3211"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.4374000132083893,"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":0.4374000132083893,"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":0.08760000020265579,"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"}},{"id":"https://openalex.org/T13702","display_name":"Machine Learning in Healthcare","score":0.024700000882148743,"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/path","display_name":"Path (computing)","score":0.423799991607666},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.30709999799728394},{"id":"https://openalex.org/keywords/modeling-language","display_name":"Modeling language","score":0.29829999804496765},{"id":"https://openalex.org/keywords/language-model","display_name":"Language model","score":0.289900004863739},{"id":"https://openalex.org/keywords/action","display_name":"Action (physics)","score":0.28209999203681946},{"id":"https://openalex.org/keywords/natural-language","display_name":"Natural language","score":0.2766000032424927}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6377999782562256},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.45239999890327454},{"id":"https://openalex.org/C2777735758","wikidata":"https://www.wikidata.org/wiki/Q817765","display_name":"Path (computing)","level":2,"score":0.423799991607666},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.33880001306533813},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.30709999799728394},{"id":"https://openalex.org/C179603123","wikidata":"https://www.wikidata.org/wiki/Q1941921","display_name":"Modeling language","level":3,"score":0.29829999804496765},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.289900004863739},{"id":"https://openalex.org/C2780791683","wikidata":"https://www.wikidata.org/wiki/Q846785","display_name":"Action (physics)","level":2,"score":0.28209999203681946},{"id":"https://openalex.org/C195324797","wikidata":"https://www.wikidata.org/wiki/Q33742","display_name":"Natural language","level":2,"score":0.2766000032424927},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.26489999890327454},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.25760000944137573},{"id":"https://openalex.org/C161301231","wikidata":"https://www.wikidata.org/wiki/Q3478658","display_name":"Knowledge representation and reasoning","level":2,"score":0.2549000084400177}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18653/v1/2025.findings-emnlp.170","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2025.findings-emnlp.170","pdf_url":"https://aclanthology.org/2025.findings-emnlp.170.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: EMNLP 2025","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.18653/v1/2025.findings-emnlp.170","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2025.findings-emnlp.170","pdf_url":"https://aclanthology.org/2025.findings-emnlp.170.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: EMNLP 2025","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"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/W4416035175.pdf","grobid_xml":"https://content.openalex.org/works/W4416035175.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Recent":[0],"advances":[1],"in":[2],"Large":[3],"Language":[4],"Models":[5],"(LLMs)":[6],"have":[7],"highlighted":[8],"the":[9,110],"challenge":[10],"of":[11,112],"handling":[12],"long-context":[13,40,57,102,107],"tasks,":[14,48],"where":[15],"models":[16,74],"need":[17],"to":[18,24,75,89],"reason":[19],"over":[20,118],"extensive":[21],"input":[22],"contexts":[23],"aggregate":[25],"target":[26],"information.While":[27],"Chain-of-Thought":[28],"(CoT)":[29],"prompting":[30],"has":[31],"shown":[32],"promise":[33],"for":[34,39,80,101,130],"multi-step":[35],"reasoning,":[36],"its":[37],"effectiveness":[38,111],"scenarios":[41,58],"remains":[42],"underexplored.Through":[43],"systematic":[44],"investigation":[45],"across":[46,55,143],"diverse":[47,144],"we":[49,67],"demonstrate":[50,109],"that":[51,72],"CoT's":[52],"benefits":[53],"generalize":[54],"most":[56],"and":[59,93,127,134,138,150],"amplify":[60],"with":[61],"increasing":[62],"context":[63],"length.Motivated":[64],"by":[65],"this,":[66],"propose":[68],"a":[69,86,94],"process-supervised":[70],"framework":[71,84],"teaches":[73],"generate":[76],"high-quality":[77],"reasoning":[78,91],"paths":[79,92],"enhanced":[81],"longcontext":[82],"performance.Our":[83],"incorporates":[85],"self-sampling":[87],"mechanism":[88],"bootstrap":[90],"novel":[95],"quality":[96],"assessment":[97],"protocol":[98],"specifically":[99],"designed":[100],"scenarios.Experimental":[103],"results":[104],"on":[105,122,132,141],"various":[106],"benchmarks":[108],"our":[113,148],"approach,":[114],"achieving":[115],"significant":[116],"improvements":[117],"outcome":[119],"supervision":[120],"baselines":[121],"both":[123],"in-domain":[124],"tasks":[125],"(+13.6,+3.8":[126],"+7.5":[128],"points":[129,140],"LLaMA/Qwen":[131],"MuSiQue)":[133],"cross-domain":[135],"generalization":[136],"(+9.3,+8.1":[137],"+10.4":[139],"average":[142],"QA":[145],"tasks).We":[146],"release":[147],"code":[149],"dataset":[151],"at":[152],"https://github.com/":[153],"lemon-prog123/LongRePS.":[154]},"counts_by_year":[{"year":2026,"cited_by_count":2}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-11-08T00:00:00"}