{"id":"https://openalex.org/W7166820555","doi":"https://doi.org/10.18653/v1/2026.acl-long.1013","title":"Efficient Prior-Guided Reasoning for Robust Retrieval-Augmented Generation under Conflicts","display_name":"Efficient Prior-Guided Reasoning for Robust Retrieval-Augmented Generation under Conflicts","publication_year":2026,"publication_date":"2026-01-01","ids":{"openalex":"https://openalex.org/W7166820555","doi":"https://doi.org/10.18653/v1/2026.acl-long.1013"},"language":null,"primary_location":{"id":"doi:10.18653/v1/2026.acl-long.1013","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2026.acl-long.1013","pdf_url":"https://aclanthology.org/2026.acl-long.1013.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.1013.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5139824360","display_name":"Xiaowei Yuan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xiaowei Yuan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139798866","display_name":"Ziyang Huang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ziyang Huang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5127202425","display_name":"Zhao Yang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhao Yang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5029640741","display_name":"Yequan Wang","orcid":"https://orcid.org/0000-0001-7530-6125"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yequan Wang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139735441","display_name":"Jun Zhao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jun Zhao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5139757024","display_name":"Kang Liu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kang Liu","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":0.84764742,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"22149","last_page":"22164"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11596","display_name":"Constraint Satisfaction and Optimization","score":0.33730000257492065,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T11596","display_name":"Constraint Satisfaction and Optimization","score":0.33730000257492065,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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":0.0617000013589859,"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/T10286","display_name":"Information Retrieval and Search Behavior","score":0.04410000145435333,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.26409998536109924},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.26249998807907104},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.2615000009536743},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.2500999867916107},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.23520000278949738}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.557699978351593},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4142000079154968},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.26409998536109924},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.26249998807907104},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.2615000009536743},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.2500999867916107},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.23520000278949738},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.23409999907016754},{"id":"https://openalex.org/C527412718","wikidata":"https://www.wikidata.org/wiki/Q855395","display_name":"Interpretation (philosophy)","level":2,"score":0.2329999953508377},{"id":"https://openalex.org/C18762648","wikidata":"https://www.wikidata.org/wiki/Q42213","display_name":"Work (physics)","level":2,"score":0.23119999468326569}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18653/v1/2026.acl-long.1013","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2026.acl-long.1013","pdf_url":"https://aclanthology.org/2026.acl-long.1013.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.1013","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2026.acl-long.1013","pdf_url":"https://aclanthology.org/2026.acl-long.1013.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":[{"id":"https://openalex.org/G5208670511","display_name":null,"funder_award_id":"U24A20335","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/W7166820555.pdf","grobid_xml":"https://content.openalex.org/works/W7166820555.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Retrieval-Augmented":[0],"Generation":[1],"(RAG)":[2],"has":[3],"become":[4],"a":[5,73,87],"standard":[6],"paradigm":[7],"for":[8,70],"grounding":[9],"Large":[10],"Language":[11],"Models":[12],"(LLMs)":[13],"with":[14,24],"external":[15,60,83,121],"knowledge.However,":[16],"RAG":[17],"performance":[18,78],"often":[19],"degrades":[20],"substantially":[21],"when":[22],"faced":[23],"noisy,":[25],"outdated,":[26],"or":[27],"conflicting":[28],"retrieved":[29,54],"information.In":[30],"this":[31],"work,":[32],"we":[33,64],"empirically":[34],"demonstrate":[35,113],"that":[36,40,75,114],"Prior-Guided":[37,71],"Reasoning-a":[38],"strategy":[39],"explicitly":[41],"elicits":[42],"the":[43,57,95,100],"model's":[44],"parametric":[45],"knowledge":[46],"as":[47],"prior":[48,109],"information":[49],"to":[50,120],"guide":[51],"reasoning":[52,97,106],"on":[53,62],"documents-effectively":[55],"mitigates":[56],"impact":[58],"of":[59,82],"conflicts.Building":[61],"this,":[63],"propose":[65],"BrPr":[66,93,115],"(Bernoulligated":[67],"reinforcement":[68],"learning":[69],"reasoning),":[72],"framework":[74],"achieves":[76],"robust":[77],"across":[79],"varying":[80],"degrees":[81],"inconsistency.Furthermore,":[84],"by":[85],"employing":[86],"Bernoulli-gated":[88],"dropout":[89],"mechanism":[90],"during":[91],"training,":[92],"distills":[94],"prior-driven":[96],"capability":[98],"into":[99],"model":[101],"parameters,":[102],"enabling":[103],"efficient":[104],"latent":[105],"without":[107],"explicit":[108],"generation.The":[110],"experimental":[111],"results":[112],"consistently":[116],"exhibits":[117],"superior":[118],"robustness":[119],"conflicts":[122],"and":[123],"noise.":[124]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2026-07-02T00:00:00"}
