{"id":"https://openalex.org/W4412944667","doi":"https://doi.org/10.18653/v1/2025.findings-acl.1269","title":"KARPA: A Training-free Method of Adapting Knowledge Graph as References for Large Language Model\u2019s Reasoning Path Aggregation","display_name":"KARPA: A Training-free Method of Adapting Knowledge Graph as References for Large Language Model\u2019s Reasoning Path Aggregation","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4412944667","doi":"https://doi.org/10.18653/v1/2025.findings-acl.1269"},"language":"en","primary_location":{"id":"doi:10.18653/v1/2025.findings-acl.1269","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2025.findings-acl.1269","pdf_url":"https://aclanthology.org/2025.findings-acl.1269.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.1269.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5108935135","display_name":"Siyuan Fang","orcid":"https://orcid.org/0009-0005-5898-9522"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Siyuan Fang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5104271836","display_name":"Kaijing Ma","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kaijing Ma","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101578267","display_name":"Tianyu Zheng","orcid":"https://orcid.org/0000-0003-0847-414X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tianyu Zheng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5111762412","display_name":"Xeron Du","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xeron Du","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5029071585","display_name":"Nan L\u00fc","orcid":"https://orcid.org/0000-0003-0590-7173"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ningxuan Lu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100326077","display_name":"Ge Zhang","orcid":"https://orcid.org/0000-0003-0704-0657"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ge Zhang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":null,"display_name":"Qingkun Tang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Qingkun Tang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":7,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":3.5175,"has_fulltext":true,"cited_by_count":2,"citation_normalized_percentile":{"value":0.93096283,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"24724","last_page":"24746"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9787999987602234,"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":0.9787999987602234,"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":0.9740999937057495,"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":0.9208999872207642,"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/computer-science","display_name":"Computer science","score":0.7927614450454712},{"id":"https://openalex.org/keywords/path","display_name":"Path (computing)","score":0.608127772808075},{"id":"https://openalex.org/keywords/knowledge-graph","display_name":"Knowledge graph","score":0.5575262904167175},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5169867277145386},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5101635456085205},{"id":"https://openalex.org/keywords/language-model","display_name":"Language model","score":0.5015912055969238},{"id":"https://openalex.org/keywords/training","display_name":"Training (meteorology)","score":0.4920627474784851},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.39794594049453735},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.36521100997924805},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.2127179205417633},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.15758511424064636}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7927614450454712},{"id":"https://openalex.org/C2777735758","wikidata":"https://www.wikidata.org/wiki/Q817765","display_name":"Path (computing)","level":2,"score":0.608127772808075},{"id":"https://openalex.org/C2987255567","wikidata":"https://www.wikidata.org/wiki/Q33002955","display_name":"Knowledge graph","level":2,"score":0.5575262904167175},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5169867277145386},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5101635456085205},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.5015912055969238},{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.4920627474784851},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.39794594049453735},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.36521100997924805},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.2127179205417633},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.15758511424064636},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18653/v1/2025.findings-acl.1269","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2025.findings-acl.1269","pdf_url":"https://aclanthology.org/2025.findings-acl.1269.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.1269","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2025.findings-acl.1269","pdf_url":"https://aclanthology.org/2025.findings-acl.1269.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":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4412944667.pdf","grobid_xml":"https://content.openalex.org/works/W4412944667.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W230091440","https://openalex.org/W2233261550","https://openalex.org/W2810751659","https://openalex.org/W258997015","https://openalex.org/W2997094352","https://openalex.org/W4412817058","https://openalex.org/W3216976533","https://openalex.org/W100620283","https://openalex.org/W2495260952","https://openalex.org/W4366179611"],"abstract_inverted_index":{"Large":[0],"language":[1],"models":[2],"(LLMs)":[3],"demonstrate":[4],"exceptional":[5],"performance":[6,156],"across":[7],"a":[8,34,85],"variety":[9],"of":[10,22,62,94],"tasks,":[11,159],"yet":[12],"they":[13,65],"are":[14,47],"often":[15,48],"affected":[16],"by":[17,50],"hallucinations":[18],"and":[19,59,98,123,142,164],"the":[20,56,90,110],"timeliness":[21],"knowledge.Leveraging":[23],"knowledge":[24,29,42],"graphs":[25],"(KGs)":[26],"as":[27,33],"external":[28],"sources":[30],"has":[31],"emerged":[32],"viable":[35],"solution,":[36],"but":[37],"existing":[38,131],"methods":[39],"for":[40,96],"LLM-based":[41],"graph":[43,79],"question":[44],"answering":[45],"(KGQA)":[46],"limited":[49],"step-by-step":[51],"decision-making":[52],"on":[53,70,169],"KGs,":[54],"restricting":[55],"global":[57,91,112],"planning":[58,92,113],"reasoning":[60,124],"capabilities":[61],"LLMs,":[63],"or":[64,68],"require":[66],"fine-tuning":[67],"pre-training":[69],"specific":[71],"KGs.To":[72],"address":[73],"these":[74,126],"challenges,":[75],"we":[76],"propose":[77],"Knowledge":[78],"Assisted":[80],"Reasoning":[81],"Path":[82],"Aggregation":[83],"(KARPA),":[84],"novel":[86],"framework":[87],"that":[88,152],"harnesses":[89],"abilities":[93],"LLMs":[95],"efficient":[97],"accurate":[99],"KG":[100],"reasoning.KARPA":[101],"operates":[102],"in":[103,157],"three":[104],"steps:":[105],"pre-planning":[106],"relation":[107],"paths":[108,118,127],"using":[109],"LLM's":[111],"capabilities,":[114],"matching":[115],"semantically":[116],"relevant":[117],"via":[119],"an":[120],"embedding":[121],"model,":[122],"over":[125],"to":[128,145],"generate":[129],"answers.Unlike":[130],"KGQA":[132,158],"methods,":[133],"KARPA":[134,153],"avoids":[135],"stepwise":[136],"traversal,":[137],"requires":[138],"no":[139],"additional":[140],"training,":[141],"is":[143,167],"adaptable":[144],"various":[146],"LLM":[147],"architectures.Extensive":[148],"experimental":[149],"results":[150],"show":[151],"achieves":[154],"state-of-the-art":[155],"delivering":[160],"both":[161],"high":[162],"efficiency":[163],"accuracy.Our":[165],"code":[166],"available":[168],"GitHub.":[170]},"counts_by_year":[{"year":2025,"cited_by_count":2}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}