{"id":"https://openalex.org/W4412888523","doi":"https://doi.org/10.18653/v1/2025.findings-acl.436","title":"FiDeLiS: Faithful Reasoning in Large Language Models for Knowledge Graph Question Answering","display_name":"FiDeLiS: Faithful Reasoning in Large Language Models for Knowledge Graph Question Answering","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4412888523","doi":"https://doi.org/10.18653/v1/2025.findings-acl.436"},"language":"en","primary_location":{"id":"doi:10.18653/v1/2025.findings-acl.436","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2025.findings-acl.436","pdf_url":"https://aclanthology.org/2025.findings-acl.436.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.436.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101399147","display_name":"Yuan Sui","orcid":"https://orcid.org/0000-0001-8559-831X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yuan Sui","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102676899","display_name":"Yufei He","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yufei He","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100377352","display_name":"Nian Liu","orcid":"https://orcid.org/0000-0002-0825-6081"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Nian Liu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5111408164","display_name":"X. He","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xiaoxin He","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100366692","display_name":"Kun Wang","orcid":"https://orcid.org/0000-0002-9099-2781"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kun Wang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5065675832","display_name":"Bryan Hooi","orcid":"https://orcid.org/0000-0002-5645-1754"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Bryan Hooi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":6,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":19.3465,"has_fulltext":true,"cited_by_count":11,"citation_normalized_percentile":{"value":0.99176741,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"8315","last_page":"8330"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9940000176429749,"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":0.9940000176429749,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.9902999997138977,"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/T11719","display_name":"Data Quality and Management","score":0.9714999794960022,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/question-answering","display_name":"Question answering","score":0.7204948663711548},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6496304869651794},{"id":"https://openalex.org/keywords/knowledge-graph","display_name":"Knowledge graph","score":0.4848679006099701},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4507168233394623},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.43615034222602844},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.38013947010040283},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.33201444149017334},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.2188701629638672},{"id":"https://openalex.org/keywords/philosophy","display_name":"Philosophy","score":0.13087329268455505}],"concepts":[{"id":"https://openalex.org/C44291984","wikidata":"https://www.wikidata.org/wiki/Q1074173","display_name":"Question answering","level":2,"score":0.7204948663711548},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6496304869651794},{"id":"https://openalex.org/C2987255567","wikidata":"https://www.wikidata.org/wiki/Q33002955","display_name":"Knowledge graph","level":2,"score":0.4848679006099701},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4507168233394623},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.43615034222602844},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.38013947010040283},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.33201444149017334},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.2188701629638672},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.13087329268455505}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18653/v1/2025.findings-acl.436","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2025.findings-acl.436","pdf_url":"https://aclanthology.org/2025.findings-acl.436.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.436","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2025.findings-acl.436","pdf_url":"https://aclanthology.org/2025.findings-acl.436.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":[{"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4","score":0.41999998688697815}],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4412888523.pdf","grobid_xml":"https://content.openalex.org/works/W4412888523.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2384605597","https://openalex.org/W2387743295","https://openalex.org/W3082787378","https://openalex.org/W2136007095","https://openalex.org/W2366230879","https://openalex.org/W3208425359","https://openalex.org/W2349927912","https://openalex.org/W3159777597","https://openalex.org/W4212839359","https://openalex.org/W4401140950"],"abstract_inverted_index":{"Large":[0],"Language":[1],"Models":[2],"(LLMs)":[3],"are":[4],"often":[5],"challenged":[6],"by":[7,68,98,129],"generating":[8],"erroneous":[9],"or":[10,36],"hallucinated":[11],"responses,":[12],"especially":[13],"in":[14,40],"complex":[15],"reasoning":[16,73,95],"tasks.Leveraging":[17],"Knowledge":[18],"Graphs":[19],"(KGs)":[20],"as":[21,27,139],"external":[22],"knowledge":[23,43],"sources":[24],"has":[25],"emerged":[26],"a":[28,54,86,112,117,140],"viable":[29],"solution.However,":[30],"existing":[31],"KGenhanced":[32],"methods,":[33],"either":[34],"retrieval-based":[35],"agent-based,":[37],"encounter":[38],"difficulties":[39],"accurately":[41],"retrieving":[42],"and":[44,100,153],"efficiently":[45],"traversing":[46],"KGs":[47],"at":[48],"scale.In":[49],"this":[50],"paper,":[51],"we":[52,80,110],"propose":[53,111],"unified":[55],"framework,":[56,142],"FiDeLiS":[57],"1":[58],",":[59],"designed":[60],"to":[61,71,93,115],"improve":[62,145],"the":[63,91,102,105,131,146,151],"factuality":[64,152],"of":[65],"LLM":[66,92],"responses":[67],"anchoring":[69],"answers":[70],"verifiable":[72],"steps":[74],"retrieved":[75],"from":[76],"KGs.To":[77],"achieve":[78],"this,":[79],"leverage":[81],"stepwise":[82],"beam":[83,123],"search":[84,103,124,132],"with":[85],"deductive":[87],"scoring":[88],"function,":[89],"allowing":[90],"validate":[94],"process":[96],"step":[97],"step,":[99,125],"halt":[101],"once":[104],"question":[106],"is":[107],"deducible.In":[108],"addition,":[109],"Path-RAG":[113],"module":[114],"pre-select":[116],"smaller":[118],"candidate":[119],"set":[120],"for":[121],"each":[122],"reducing":[126],"computational":[127],"costs":[128],"narrowing":[130],"space.Extensive":[133],"experiments":[134],"show":[135],"that":[136],"our":[137],"method,":[138],"training-free":[141],"not":[143],"only":[144],"performance":[147],"but":[148],"also":[149],"enhance":[150],"interpretability":[154],"across":[155],"different":[156],"benchmarks.":[157]},"counts_by_year":[{"year":2026,"cited_by_count":6},{"year":2025,"cited_by_count":5}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}