{"id":"https://openalex.org/W7166858113","doi":"https://doi.org/10.18653/v1/2026.acl-long.1692","title":"CHAIRO: Contextual Hierarchical Analogical Induction and Reasoning Optimization for LLMs","display_name":"CHAIRO: Contextual Hierarchical Analogical Induction and Reasoning Optimization for LLMs","publication_year":2026,"publication_date":"2026-01-01","ids":{"openalex":"https://openalex.org/W7166858113","doi":"https://doi.org/10.18653/v1/2026.acl-long.1692"},"language":null,"primary_location":{"id":"doi:10.18653/v1/2026.acl-long.1692","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2026.acl-long.1692","pdf_url":"https://aclanthology.org/2026.acl-long.1692.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":"Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://aclanthology.org/2026.acl-long.1692.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5054515379","display_name":"H. Lu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Haotian Lu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5113046331","display_name":"Yuchen Mou","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yuchen Mou","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5040323946","display_name":"Bingzhe Wu","orcid":"https://orcid.org/0000-0001-9598-7642"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Bingzhe Wu","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":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.85572095,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"36526","last_page":"36537"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10538","display_name":"Data Mining Algorithms and Applications","score":0.12849999964237213,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T10538","display_name":"Data Mining Algorithms and Applications","score":0.12849999964237213,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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":0.07159999758005142,"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/T10906","display_name":"AI-based Problem Solving and Planning","score":0.0681999996304512,"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/analogical-reasoning","display_name":"Analogical reasoning","score":0.30640000104904175},{"id":"https://openalex.org/keywords/case-based-reasoning","display_name":"Case-based reasoning","score":0.30079999566078186},{"id":"https://openalex.org/keywords/deductive-reasoning","display_name":"Deductive reasoning","score":0.24899999797344208},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.24860000610351562}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.492900013923645},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4681999981403351},{"id":"https://openalex.org/C2985612853","wikidata":"https://www.wikidata.org/wiki/Q185816","display_name":"Analogical reasoning","level":3,"score":0.30640000104904175},{"id":"https://openalex.org/C20162079","wikidata":"https://www.wikidata.org/wiki/Q1151406","display_name":"Case-based reasoning","level":2,"score":0.30079999566078186},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.2847999930381775},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.27900001406669617},{"id":"https://openalex.org/C188147891","wikidata":"https://www.wikidata.org/wiki/Q147638","display_name":"Cognitive science","level":1,"score":0.26510000228881836},{"id":"https://openalex.org/C97364631","wikidata":"https://www.wikidata.org/wiki/Q484284","display_name":"Deductive reasoning","level":2,"score":0.24899999797344208},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.24860000610351562},{"id":"https://openalex.org/C180747234","wikidata":"https://www.wikidata.org/wiki/Q23373","display_name":"Cognitive psychology","level":1,"score":0.24819999933242798}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18653/v1/2026.acl-long.1692","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2026.acl-long.1692","pdf_url":"https://aclanthology.org/2026.acl-long.1692.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":"Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.18653/v1/2026.acl-long.1692","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2026.acl-long.1692","pdf_url":"https://aclanthology.org/2026.acl-long.1692.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":"Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7166858113.pdf","grobid_xml":"https://content.openalex.org/works/W7166858113.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Warning:":[0],"This":[1],"paper":[2],"may":[3],"contain":[4],"content":[5,26,108,169],"that":[6,76,114,146,159],"could":[7],"be":[8],"disturbing":[9],"or":[10,52,65],"offensive.Content":[11],"moderation":[12,48,74,97,104,131,170],"in":[13,39,128,171],"online":[14],"platforms":[15],"faces":[16],"persistent":[17],"challenges":[18],"due":[19],"to":[20,63,80,106],"the":[21,28,100],"evolving":[22],"complexity":[23],"of":[24,30,91,103,130],"user-generated":[25],"and":[27,33,61,84,96,123,133,140,155,167],"limitations":[29],"traditional":[31],"rule-based":[32],"machine":[34],"learning":[35],"approaches.While":[36],"recent":[37],"advances":[38],"large":[40],"language":[41],"models":[42],"(LLMs)":[43],"have":[44],"enabled":[45],"more":[46],"sophisticated":[47],"via":[49],"direct":[50],"prompting":[51],"fine-tuning,":[53],"these":[54],"approaches":[55],"often":[56],"exhibit":[57],"limited":[58],"generalization,":[59],"interpretability,":[60,154],"adaptability":[62],"unseen":[64],"ambiguous":[66],"cases.In":[67],"this":[68],"work,":[69],"we":[70,112],"propose":[71],"a":[72],"novel":[73],"framework":[75,148],"leverages":[77],"analogical":[78,92,160],"examples":[79],"enhance":[81],"rule":[82,94,134],"induction":[83],"decision":[85],"reliability.Our":[86],"approach":[87],"integrates":[88],"end-to-end":[89],"optimization":[90],"retrieval,":[93],"generation,":[95],"classification,":[98],"enabling":[99],"dynamic":[101],"adaptation":[102],"rules":[105,150],"diverse":[107],"scenarios.Through":[109],"comprehensive":[110],"experiments,":[111],"demonstrate":[113],"our":[115,147],"method":[116],"significantly":[117],"outperforms":[118],"both":[119],"rule-injected":[120],"finetuning":[121],"baselines":[122],"multi-stage":[124],"static":[125],"RAG":[126],"pipelines":[127],"terms":[129],"accuracy":[132],"quality.Further":[135],"evaluations,":[136],"including":[137],"human":[138],"assessments":[139],"external":[141],"model":[142],"generalization":[143],"tests,":[144],"confirm":[145],"produces":[149],"with":[151],"better":[152],"clarity,":[153],"applicability.These":[156],"findings":[157],"show":[158],"example-driven":[161],"methods":[162],"can":[163],"advance":[164],"robust,":[165],"explainable,":[166],"generalizable":[168],"real-world":[172],"applications.":[173]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2026-07-02T00:00:00"}