{"id":"https://openalex.org/W7140094780","doi":"https://doi.org/10.18653/v1/2026.findings-eacl.184","title":"Conformal Feedback Alignment: Quantifying Answer-Level Reliability for Robust LLM Alignment","display_name":"Conformal Feedback Alignment: Quantifying Answer-Level Reliability for Robust LLM Alignment","publication_year":2026,"publication_date":"2026-01-01","ids":{"openalex":"https://openalex.org/W7140094780","doi":"https://doi.org/10.18653/v1/2026.findings-eacl.184"},"language":null,"primary_location":{"id":"doi:10.18653/v1/2026.findings-eacl.184","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2026.findings-eacl.184","pdf_url":"https://aclanthology.org/2026.findings-eacl.184.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: EACL 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-eacl.184.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5130349457","display_name":"Tiejin Chen","orcid":null},"institutions":[{"id":"https://openalex.org/I55732556","display_name":"Arizona State University","ror":"https://ror.org/03efmqc40","country_code":"US","type":"education","lineage":["https://openalex.org/I55732556"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Tiejin Chen","raw_affiliation_strings":["Arizona State University Arizona State University Arizona State University Arizona State University Arizona State University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Arizona State University Arizona State University Arizona State University Arizona State University Arizona State University","institution_ids":["https://openalex.org/I55732556"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130335789","display_name":"Xiaoou Liu","orcid":null},"institutions":[{"id":"https://openalex.org/I55732556","display_name":"Arizona State University","ror":"https://ror.org/03efmqc40","country_code":"US","type":"education","lineage":["https://openalex.org/I55732556"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xiaoou Liu","raw_affiliation_strings":["Arizona State University Arizona State University Arizona State University Arizona State University Arizona State University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Arizona State University Arizona State University Arizona State University Arizona State University Arizona State University","institution_ids":["https://openalex.org/I55732556"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130411486","display_name":"Vishnu Nandam","orcid":null},"institutions":[{"id":"https://openalex.org/I55732556","display_name":"Arizona State University","ror":"https://ror.org/03efmqc40","country_code":"US","type":"education","lineage":["https://openalex.org/I55732556"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Vishnu Nandam","raw_affiliation_strings":["Arizona State University Arizona State University Arizona State University Arizona State University Arizona State University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Arizona State University Arizona State University Arizona State University Arizona State University Arizona State University","institution_ids":["https://openalex.org/I55732556"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5109809205","display_name":"K. N. Liou","orcid":null},"institutions":[{"id":"https://openalex.org/I55732556","display_name":"Arizona State University","ror":"https://ror.org/03efmqc40","country_code":"US","type":"education","lineage":["https://openalex.org/I55732556"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kuan-Ru Liou","raw_affiliation_strings":["Arizona State University Arizona State University Arizona State University Arizona State University Arizona State University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Arizona State University Arizona State University Arizona State University Arizona State University Arizona State University","institution_ids":["https://openalex.org/I55732556"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5130349459","display_name":"Hua Wei","orcid":null},"institutions":[{"id":"https://openalex.org/I55732556","display_name":"Arizona State University","ror":"https://ror.org/03efmqc40","country_code":"US","type":"education","lineage":["https://openalex.org/I55732556"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hua Wei","raw_affiliation_strings":["Arizona State University Arizona State University Arizona State University Arizona State University Arizona State University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Arizona State University Arizona State University Arizona State University Arizona State University Arizona State University","institution_ids":["https://openalex.org/I55732556"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I55732556"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"3561","last_page":"3572"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10201","display_name":"Speech Recognition and Synthesis","score":0.25279998779296875,"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/T10201","display_name":"Speech Recognition and Synthesis","score":0.25279998779296875,"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/T10028","display_name":"Topic Modeling","score":0.1543000042438507,"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/T10181","display_name":"Natural Language Processing Techniques","score":0.0997999981045723,"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/reliability","display_name":"Reliability (semiconductor)","score":0.6502000093460083},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.39100000262260437},{"id":"https://openalex.org/keywords/control-theory","display_name":"Control theory (sociology)","score":0.38589999079704285},{"id":"https://openalex.org/keywords/conformal-map","display_name":"Conformal map","score":0.34769999980926514},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.2824000120162964}],"concepts":[{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.6502000093460083},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5471000075340271},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.39100000262260437},{"id":"https://openalex.org/C47446073","wikidata":"https://www.wikidata.org/wiki/Q5165890","display_name":"Control theory (sociology)","level":3,"score":0.38589999079704285},{"id":"https://openalex.org/C98214594","wikidata":"https://www.wikidata.org/wiki/Q850275","display_name":"Conformal map","level":2,"score":0.34769999980926514},{"id":"https://openalex.org/C200601418","wikidata":"https://www.wikidata.org/wiki/Q2193887","display_name":"Reliability engineering","level":1,"score":0.3190000057220459},{"id":"https://openalex.org/C133731056","wikidata":"https://www.wikidata.org/wiki/Q4917288","display_name":"Control engineering","level":1,"score":0.29910001158714294},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.2953000068664551},{"id":"https://openalex.org/C24326235","wikidata":"https://www.wikidata.org/wiki/Q126095","display_name":"Electronic engineering","level":1,"score":0.2854999899864197},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.2824000120162964},{"id":"https://openalex.org/C18762648","wikidata":"https://www.wikidata.org/wiki/Q42213","display_name":"Work (physics)","level":2,"score":0.2741999924182892},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.26989999413490295},{"id":"https://openalex.org/C17500928","wikidata":"https://www.wikidata.org/wiki/Q959968","display_name":"Control system","level":2,"score":0.26100000739097595}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18653/v1/2026.findings-eacl.184","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2026.findings-eacl.184","pdf_url":"https://aclanthology.org/2026.findings-eacl.184.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: EACL 2026","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.18653/v1/2026.findings-eacl.184","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2026.findings-eacl.184","pdf_url":"https://aclanthology.org/2026.findings-eacl.184.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: EACL 2026","raw_type":"proceedings-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/13","score":0.48332589864730835,"display_name":"Climate action"}],"awards":[{"id":"https://openalex.org/G8707547214","display_name":"CAREER: The Next Frontier in Urban Data Analytics: From Prescriptive to Actionable","funder_award_id":"2442477","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320307791","display_name":"Cisco Systems","ror":"https://ror.org/03yt1ez60"},{"id":"https://openalex.org/F4320309835","display_name":"Arizona State University","ror":"https://ror.org/03efmqc40"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7140094780.pdf","grobid_xml":"https://content.openalex.org/works/W7140094780.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Preference-based":[0],"alignment":[1,91],"like":[2],"Reinforcement":[3],"Learning":[4],"from":[5,10],"Human":[6],"Feedback":[7,44],"(RLHF)":[8],"learns":[9],"pairwise":[11],"preferences,":[12,24],"yet":[13],"the":[14,31,34,39,54],"labels":[15],"are":[16,110],"often":[17],"noisy":[18],"and":[19,72,93,104],"inconsistent.Existing":[20],"uncertainty-aware":[21],"approaches":[22],"weight":[23],"but":[25],"ignore":[26],"a":[27,47],"more":[28,106],"fundamental":[29],"factor:":[30],"reliability":[32,63],"of":[33,57],"answers":[35],"being":[36],"compared.To":[37],"address":[38],"problem,":[40],"we":[41],"propose":[42],"Conformal":[43,58],"Alignment":[45],"(CFA),":[46],"framework":[48],"that":[49,88,97],"grounds":[50],"preference":[51],"weighting":[52,103],"in":[53],"statistical":[55],"guarantees":[56],"Prediction":[59],"(CP).CFA":[60],"quantifies":[61],"answer-level":[62],"by":[64],"constructing":[65],"conformal":[66],"prediction":[67],"sets":[68],"with":[69],"controllable":[70],"coverage":[71],"aggregates":[73],"these":[74],"reliabilities":[75],"into":[76],"principled":[77],"weights":[78],"for":[79],"both":[80],"DPOand":[81],"PPO-style":[82],"training.Experiments":[83],"across":[84],"different":[85],"datasets":[86],"show":[87],"CFA":[89],"improves":[90],"robustness":[92],"data":[94],"efficiency,":[95],"highlighting":[96],"modeling":[98],"answer-side":[99],"uncertainty":[100],"complements":[101],"preference-level":[102],"yields":[105],"robust,":[107],"data-efficient":[108],"alignment.Codes":[109],"provided":[111],"on":[112],"https://github.com/tiejin98/":[113],"Conformal-Feedback":[114]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2026-03-24T00:00:00"}
