{"id":"https://openalex.org/W7166889897","doi":"https://doi.org/10.18653/v1/2026.acl-long.743","title":"Biomedical Question Answering via Multi-Level Summarization on a Local Knowledge Graph","display_name":"Biomedical Question Answering via Multi-Level Summarization on a Local Knowledge Graph","publication_year":2026,"publication_date":"2026-01-01","ids":{"openalex":"https://openalex.org/W7166889897","doi":"https://doi.org/10.18653/v1/2026.acl-long.743"},"language":"en","primary_location":{"id":"doi:10.18653/v1/2026.acl-long.743","doi":"https://doi.org/10.18653/v1/2026.acl-long.743","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2026.acl-long.743","pdf_url":"https://aclanthology.org/2026.acl-long.743.pdf","source":{"id":"https://openalex.org/S4393915740","display_name":"Proceedings of the conference - Association for Computational Linguistics. Meeting","issn_l":"0736-587X","issn":["0736-587X"],"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":["norway-1"],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"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"},"volume":null,"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://aclanthology.org/2026.acl-long.743.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5107957713","display_name":"Lingxiao Guan","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I27837315","display_name":"University of Michigan","ror":"https://ror.org/00jmfr291","country_code":"US","type":"education","lineage":["https://openalex.org/I27837315"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Lingxiao Guan","raw_affiliation_strings":["Department of Computer Science and Engineering , University of Michigan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering , University of Michigan","institution_ids":["https://openalex.org/I27837315"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139777778","display_name":"Yuanhao Huang","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I27837315","display_name":"University of Michigan","ror":"https://ror.org/00jmfr291","country_code":"US","type":"education","lineage":["https://openalex.org/I27837315"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yuanhao Huang","raw_affiliation_strings":["Department of Computational Medicine and Bioinformatics , University of Michigan {lxguan , hyhao ,"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computational Medicine and Bioinformatics , University of Michigan {lxguan , hyhao ,","institution_ids":["https://openalex.org/I27837315"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5139741572","display_name":"Jie Liu","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I27837315","display_name":"University of Michigan","ror":"https://ror.org/00jmfr291","country_code":"US","type":"education","lineage":["https://openalex.org/I27837315"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jie Liu","raw_affiliation_strings":["Department of Computational Medicine and Bioinformatics , University of Michigan {lxguan , hyhao ,","Department of Computer Science and Engineering , University of Michigan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computational Medicine and Bioinformatics , University of Michigan {lxguan , hyhao ,","institution_ids":["https://openalex.org/I27837315"]},{"raw_affiliation_string":"Department of Computer Science and Engineering , University of Michigan","institution_ids":["https://openalex.org/I27837315"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I27837315"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.41377132,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"16338","last_page":"16364"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11710","display_name":"Biomedical Text Mining and Ontologies","score":0.7163000106811523,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T11710","display_name":"Biomedical Text Mining and Ontologies","score":0.7163000106811523,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.2069000005722046,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.030700000002980232,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/biomedical-question-answering","display_name":"biomedical question answering","score":0.9860000014305115},{"id":"https://openalex.org/keywords/retrieval-augmented-generation","display_name":"retrieval-augmented generation","score":0.8489999771118164},{"id":"https://openalex.org/keywords/entity-relationships","display_name":"entity relationships","score":0.5569999814033508},{"id":"https://openalex.org/keywords/small-language-models","display_name":"small language models","score":0.7210000157356262},{"id":"https://openalex.org/keywords/claims","display_name":"claims","score":0.421999990940094}],"concepts":[{"id":"https://openalex.org/C44291984","wikidata":"https://www.wikidata.org/wiki/Q1074173","display_name":"Question answering","level":2,"score":0.6924999952316284},{"id":"https://openalex.org/C170858558","wikidata":"https://www.wikidata.org/wiki/Q1394144","display_name":"Automatic summarization","level":2,"score":0.6847000122070312},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6694999933242798},{"id":"https://openalex.org/C2987255567","wikidata":"https://www.wikidata.org/wiki/Q33002955","display_name":"Knowledge graph","level":2,"score":0.48489999771118164},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4553000032901764},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.4343999922275543},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.40389999747276306},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.3411000072956085},{"id":"https://openalex.org/C120567893","wikidata":"https://www.wikidata.org/wiki/Q1582085","display_name":"Knowledge extraction","level":2,"score":0.30140000581741333},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.29670000076293945},{"id":"https://openalex.org/C115925183","wikidata":"https://www.wikidata.org/wiki/Q1412694","display_name":"Knowledge-based systems","level":2,"score":0.27399998903274536},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.2551000118255615},{"id":"https://openalex.org/C161301231","wikidata":"https://www.wikidata.org/wiki/Q3478658","display_name":"Knowledge representation and reasoning","level":2,"score":0.2524999976158142}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18653/v1/2026.acl-long.743","doi":"https://doi.org/10.18653/v1/2026.acl-long.743","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2026.acl-long.743","pdf_url":"https://aclanthology.org/2026.acl-long.743.pdf","source":{"id":"https://openalex.org/S4393915740","display_name":"Proceedings of the conference - Association for Computational Linguistics. Meeting","issn_l":"0736-587X","issn":["0736-587X"],"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":["norway-1"],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"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.743","doi":"https://doi.org/10.18653/v1/2026.acl-long.743","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2026.acl-long.743","pdf_url":"https://aclanthology.org/2026.acl-long.743.pdf","source":{"id":"https://openalex.org/S4393915740","display_name":"Proceedings of the conference - Association for Computational Linguistics. Meeting","issn_l":"0736-587X","issn":["0736-587X"],"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":["norway-1"],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"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":[],"sustainable_development_goals_aurora":[],"study_designs":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320332161","display_name":"National Institutes of Health","ror":"https://ror.org/01cwqze88"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7166889897.pdf","grobid_xml":"https://content.openalex.org/works/W7166889897.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W7164775967","https://openalex.org/W7169541044","https://openalex.org/W7115577572","https://openalex.org/W7115613374","https://openalex.org/W4414054262","https://openalex.org/W4416238292","https://openalex.org/W7126107474","https://openalex.org/W7221020569","https://openalex.org/W4391988289","https://openalex.org/W4414817986"],"abstract_inverted_index":{"In":[0],"Question":[1],"Answering":[2],"(QA),":[3],"Retrieval":[4],"Augmented":[5],"Generation":[6],"(RAG)":[7],"has":[8],"revolutionized":[9],"performance":[10,107],"in":[11,90],"various":[12],"domains.However,":[13],"how":[14],"to":[15,31,52,71,77,99,101],"effectively":[16,82],"capture":[17,83],"multi-document":[18],"relationships":[19,87],"remains":[20],"an":[21],"open":[22],"question.This":[23],"is":[24],"particularly":[25],"critical":[26],"for":[27],"biomedical":[28,113],"tasks":[29],"due":[30],"their":[32],"reliance":[33],"on":[34,111],"information":[35],"spread":[36],"across":[37],"multiple":[38],"documents.In":[39],"this":[40],"work,":[41],"we":[42],"propose":[43],"a":[44,54,73,95,128],"novel":[45],"method":[46],"CLAIMS,":[47],"which":[48],"utilizes":[49],"propositional":[50],"claims":[51],"construct":[53],"local":[55],"knowledge":[56,69],"graph":[57,70],"from":[58,67],"retrieved":[59],"documents.Summaries":[60],"are":[61],"then":[62],"derived":[63],"via":[64],"layerwise":[65],"summarization":[66],"the":[68,91],"contextualize":[72],"small":[74],"language":[75],"model":[76],"perform":[78],"QA.The":[79],"structured":[80],"summaries":[81],"explicit":[84],"and":[85,120],"implicit":[86],"between":[88],"entities":[89],"documents,":[92],"thus":[93],"having":[94],"more":[96],"comprehensive":[97],"context":[98],"provide":[100],"LLMs.CLAIMS":[102],"achieved":[103],"comparable":[104],"or":[105],"superior":[106],"over":[108],"RAG":[109],"baselines":[110],"several":[112],"QA":[114],"benchmarks.We":[115],"also":[116],"evaluated":[117],"its":[118,134],"generalizability":[119],"each":[121],"individual":[122],"step":[123],"of":[124,131],"our":[125],"approach":[126],"with":[127],"targeted":[129],"set":[130],"metrics,":[132],"demonstrating":[133],"effectiveness.":[135]},"counts_by_year":[],"updated_date":"2026-10-29T09:56:32.521200","created_date":"2026-07-02T00:00:00"}