{"id":"https://openalex.org/W7160184733","doi":"https://doi.org/10.63317/25xhew5rnydb","title":"HOME-KGQA: A Benchmark Dataset for Multimodal Knowledge Graph Question Answering on Household Daily Activities","display_name":"HOME-KGQA: A Benchmark Dataset for Multimodal Knowledge Graph Question Answering on Household Daily Activities","publication_year":2026,"publication_date":"2026-04-30","ids":{"openalex":"https://openalex.org/W7160184733","doi":"https://doi.org/10.63317/25xhew5rnydb"},"language":null,"primary_location":{"id":"doi:10.63317/25xhew5rnydb","is_oa":false,"landing_page_url":"https://doi.org/10.63317/25xhew5rnydb","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Language Resources and Evaluation Conference","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2605.09348","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5034129458","display_name":"Shusaku Egami","orcid":"https://orcid.org/0000-0002-3821-6507"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shusaku Egami","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129274474","display_name":"Aoi Ohta","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Aoi Ohta","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5036428681","display_name":"Tomoki Tsujimura","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tomoki Tsujimura","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5045914141","display_name":"Masaki Asada","orcid":"https://orcid.org/0000-0002-7117-5962"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Masaki Asada","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135190763","display_name":"Tatsuya Ishigaki","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tatsuya Ishigaki","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135141164","display_name":"Ken Fukuda","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ken Fukuda","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135134341","display_name":"Masahiro Hamasaki","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Masahiro Hamasaki","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5135153295","display_name":"Hiroya Takamura","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hiroya Takamura","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":0.50144143,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"7845","last_page":"7856"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11714","display_name":"Multimodal Machine Learning Applications","score":0.3312000036239624,"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"}},"topics":[{"id":"https://openalex.org/T11714","display_name":"Multimodal Machine Learning Applications","score":0.3312000036239624,"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"}},{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.2806999981403351,"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":0.2547999918460846,"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/question-answering","display_name":"Question answering","score":0.6291000247001648},{"id":"https://openalex.org/keywords/knowledge-graph","display_name":"Knowledge graph","score":0.4575999975204468},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.4498000144958496},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.43059998750686646},{"id":"https://openalex.org/keywords/knowledge-based-systems","display_name":"Knowledge-based systems","score":0.3151000142097473}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6371999979019165},{"id":"https://openalex.org/C44291984","wikidata":"https://www.wikidata.org/wiki/Q1074173","display_name":"Question answering","level":2,"score":0.6291000247001648},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4991999864578247},{"id":"https://openalex.org/C2987255567","wikidata":"https://www.wikidata.org/wiki/Q33002955","display_name":"Knowledge graph","level":2,"score":0.4575999975204468},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.4498000144958496},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.43059998750686646},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3700000047683716},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.3677000105381012},{"id":"https://openalex.org/C115925183","wikidata":"https://www.wikidata.org/wiki/Q1412694","display_name":"Knowledge-based systems","level":2,"score":0.3151000142097473},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3075999915599823},{"id":"https://openalex.org/C4554734","wikidata":"https://www.wikidata.org/wiki/Q593744","display_name":"Knowledge base","level":2,"score":0.30489999055862427},{"id":"https://openalex.org/C120567893","wikidata":"https://www.wikidata.org/wiki/Q1582085","display_name":"Knowledge extraction","level":2,"score":0.30250000953674316},{"id":"https://openalex.org/C161301231","wikidata":"https://www.wikidata.org/wiki/Q3478658","display_name":"Knowledge representation and reasoning","level":2,"score":0.2915000021457672},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.27480000257492065}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.63317/25xhew5rnydb","is_oa":false,"landing_page_url":"https://doi.org/10.63317/25xhew5rnydb","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Language Resources and Evaluation Conference","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2605.09348","is_oa":true,"landing_page_url":"https://arxiv.org/abs/2605.09348","pdf_url":"https://arxiv.org/pdf/2605.09348","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2605.09348","is_oa":true,"landing_page_url":"https://arxiv.org/abs/2605.09348","pdf_url":"https://arxiv.org/pdf/2605.09348","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G999399761","display_name":null,"funder_award_id":"JP23H03688","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"}],"funders":[{"id":"https://openalex.org/F4320311508","display_name":"National Institute of Advanced Industrial Science and Technology","ror":"https://ror.org/01703db54"},{"id":"https://openalex.org/F4320334764","display_name":"Japan Society for the Promotion of Science","ror":"https://ror.org/00hhkn466"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7160184733.pdf","grobid_xml":"https://content.openalex.org/works/W7160184733.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Large":[0],"Language":[1],"Models":[2],"(LLMs)":[3],"provide":[4],"flexible":[5],"natural":[6,113],"language":[7,114],"processing":[8],"capabilities,":[9],"while":[10],"knowledge":[11,37,55],"graphs":[12],"(KGs)":[13],"offer":[14],"explicit":[15],"and":[16,31,52,75,138],"structured":[17],"knowledge.":[18],"Integrating":[19],"these":[20],"two":[21],"in":[22],"a":[23,46,72,94,101],"complementary":[24],"manner":[25],"enables":[26],"the":[27,57,145,172],"development":[28],"of":[29,104,110,175],"reliable":[30],"verifiable":[32],"AI":[33],"systems.":[34,177],"In":[35],"particular,":[36],"graph":[38,118],"question":[39],"answering":[40],"(KGQA)":[41],"has":[42],"attracted":[43],"attention":[44],"as":[45],"means":[47],"to":[48,53,71,84,123,150,154],"reduce":[49],"LLM":[50],"hallucinations":[51],"leverage":[54],"beyond":[56],"training":[58],"data.":[59],"However,":[60],"existing":[61,124,157],"KGQA":[62,96,147,176],"benchmark":[63,97],"datasets":[64,158],"are":[65],"biased":[66],"toward":[67],"encyclopedic":[68],"knowledge,":[69],"limited":[70],"single":[73],"modality,":[74],"lack":[76],"fine-grained":[77],"spatiotemporal":[78,134],"data,":[79],"which":[80],"limits":[81],"their":[82],"applicability":[83],"real-world":[85,173],"scenarios":[86],"targeted":[87],"by":[88],"Embodied":[89],"AI.":[90],"We":[91],"introduce":[92],"HOME-KGQA,":[93],"novel":[95],"dataset":[98,179],"built":[99],"on":[100,156,161],"multimodal":[102,136],"KG":[103],"daily":[105],"household":[106],"activities.":[107],"HOME-KGQA":[108],"consists":[109],"complex,":[111],"multi-hop":[112],"questions":[115,130],"paired":[116],"with":[117],"database":[119],"query":[120],"languages.":[121],"Compared":[122],"benchmarks,":[125],"it":[126],"includes":[127],"more":[128],"challenging":[129],"that":[131,144,155,167],"involve":[132],"multi-level":[133],"reasoning,":[135],"grounding,":[137],"aggregate":[139],"functions.":[140],"Experimental":[141],"results":[142],"show":[143],"LLM-based":[146],"methods":[148],"fail":[149],"achieve":[151],"performance":[152],"comparable":[153],"when":[159],"evaluated":[160],"HOME-KGQA.":[162],"This":[163],"highlights":[164],"significant":[165],"challenges":[166],"should":[168],"be":[169],"addressed":[170],"for":[171],"deployment":[174],"Our":[178],"is":[180],"available":[181],"at":[182],"https://github.com/aistairc/home-kgqa":[183]},"counts_by_year":[],"updated_date":"2026-08-01T09:00:35.917206","created_date":"2026-05-05T00:00:00"}