{"id":"https://openalex.org/W7204163897","doi":"https://doi.org/10.1145/3799682.3841078","title":"GeoRisk-RAG: A Hierarchy-Aware Risk Framework for Improving RAG Reliability through Selective Answering","display_name":"GeoRisk-RAG: A Hierarchy-Aware Risk Framework for Improving RAG Reliability through Selective Answering","publication_year":2026,"publication_date":"2026-11-03","ids":{"openalex":"https://openalex.org/W7204163897","doi":"https://doi.org/10.1145/3799682.3841078"},"language":"en","primary_location":{"id":"doi:10.1145/3799682.3841078","doi":"https://doi.org/10.1145/3799682.3841078","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3799682.3841078","pdf_url":null,"source":{"id":"https://openalex.org/S4393918199","display_name":"ACM International Conference on Information and Knowledge Management (CIKM)","issn_l":"2155-0751","issn":["2155-0751"],"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"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 35th ACM International Conference on Information and Knowledge Management","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","is_traditional":true,"indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://doi.org/10.1145/3799682.3841078","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5120267354","display_name":"Meenu Ravi","orcid":"https://orcid.org/0009-0002-0616-4674","observed_orcids":["https://orcid.org/0009-0002-0616-4674"]},"institutions":[{"id":"https://openalex.org/I859038795","display_name":"Virginia Tech","ror":"https://ror.org/02smfhw86","country_code":"US","type":"education","lineage":["https://openalex.org/I859038795"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Meenu Ravi","raw_affiliation_strings":["Virginia Tech, Alexandria, VA, USA"],"raw_orcid":"https://orcid.org/0009-0002-0616-4674","affiliations":[{"raw_affiliation_string":"Virginia Tech, Alexandria, VA, USA","institution_ids":["https://openalex.org/I859038795"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5004703367","display_name":"Shailik Sarkar","orcid":"https://orcid.org/0000-0001-6544-2262","observed_orcids":["https://orcid.org/0000-0001-6544-2262"]},"institutions":[{"id":"https://openalex.org/I32480017","display_name":"Florida Polytechnic University","ror":"https://ror.org/01e5mdj42","country_code":"US","type":"education","lineage":["https://openalex.org/I32480017"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Shailik Sarkar","raw_affiliation_strings":["Florida Polytechnic Institute, Lakeland, FL, USA"],"raw_orcid":"https://orcid.org/0000-0001-6544-2262","affiliations":[{"raw_affiliation_string":"Florida Polytechnic Institute, Lakeland, FL, USA","institution_ids":["https://openalex.org/I32480017"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057307805","display_name":"Lulwah Alkulaib","orcid":"https://orcid.org/0000-0001-9827-0882","observed_orcids":["https://orcid.org/0000-0001-9827-0882"]},"institutions":[{"id":"https://openalex.org/I36721946","display_name":"Kuwait University","ror":"https://ror.org/021e5j056","country_code":"KW","type":"education","lineage":["https://openalex.org/I36721946"]}],"countries":["KW"],"is_corresponding":false,"raw_author_name":"Lulwah Alkulaib","raw_affiliation_strings":["Kuwait University College of Science, Doha District, Kuwait"],"raw_orcid":"https://orcid.org/0000-0001-9827-0882","affiliations":[{"raw_affiliation_string":"Kuwait University College of Science, Doha District, Kuwait","institution_ids":["https://openalex.org/I36721946"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5148094862","display_name":"Yordanos Tessema","orcid":"https://orcid.org/0009-0004-2962-7904","observed_orcids":["https://orcid.org/0009-0004-2962-7904"]},"institutions":[{"id":"https://openalex.org/I859038795","display_name":"Virginia Tech","ror":"https://ror.org/02smfhw86","country_code":"US","type":"education","lineage":["https://openalex.org/I859038795"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yordanos Tessema","raw_affiliation_strings":["Virginia Tech, Alexandria, VA, USA"],"raw_orcid":"https://orcid.org/0009-0004-2962-7904","affiliations":[{"raw_affiliation_string":"Virginia Tech, Alexandria, VA, USA","institution_ids":["https://openalex.org/I859038795"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5038002204","display_name":"Chang\u2010Tien Lu","orcid":"https://orcid.org/0000-0003-3675-0199","observed_orcids":["https://orcid.org/0000-0003-3675-0199"]},"institutions":[{"id":"https://openalex.org/I859038795","display_name":"Virginia Tech","ror":"https://ror.org/02smfhw86","country_code":"US","type":"education","lineage":["https://openalex.org/I859038795"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Chang-Tien Lu","raw_affiliation_strings":["Virginia Tech, Alexandria, VA, USA"],"raw_orcid":"https://orcid.org/0000-0003-3675-0199","affiliations":[{"raw_affiliation_string":"Virginia Tech, Alexandria, VA, USA","institution_ids":["https://openalex.org/I859038795"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"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":0.0,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"4076","last_page":"4086"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9872999787330627,"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":0.9872999787330627,"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":0.0044999998062849045,"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/T10286","display_name":"Information Retrieval and Search Behavior","score":0.0027000000700354576,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/retrieval-augmented-generation","display_name":"retrieval-augmented generation","score":0.9900000095367432},{"id":"https://openalex.org/keywords/context-retrieval","display_name":"context retrieval","score":0.7310000061988831},{"id":"https://openalex.org/keywords/natural-hazard-management","display_name":"natural hazard management","score":0.7760000228881836},{"id":"https://openalex.org/keywords/human-preference-alignment","display_name":"human preference alignment","score":0.6650000214576721},{"id":"https://openalex.org/keywords/geospatial-question-answering","display_name":"geospatial question answering","score":0.6359999775886536}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6951000094413757},{"id":"https://openalex.org/C9770341","wikidata":"https://www.wikidata.org/wiki/Q1938983","display_name":"Geospatial analysis","level":2,"score":0.659600019454956},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.6054999828338623},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.4909999966621399},{"id":"https://openalex.org/C130318100","wikidata":"https://www.wikidata.org/wiki/Q2268914","display_name":"Semantic similarity","level":2,"score":0.4724000096321106},{"id":"https://openalex.org/C177774035","wikidata":"https://www.wikidata.org/wiki/Q1246948","display_name":"Granularity","level":2,"score":0.45890000462532043},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.44859999418258667},{"id":"https://openalex.org/C41856607","wikidata":"https://www.wikidata.org/wiki/Q483130","display_name":"Geographic information system","level":2,"score":0.44119998812675476},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.43059998750686646},{"id":"https://openalex.org/C2776654903","wikidata":"https://www.wikidata.org/wiki/Q2601463","display_name":"SAFER","level":2,"score":0.37459999322891235},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.36160001158714294},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.33709999918937683},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.33480000495910645},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.3264000117778778},{"id":"https://openalex.org/C184898388","wikidata":"https://www.wikidata.org/wiki/Q1435712","display_name":"Pairwise comparison","level":2,"score":0.3041999936103821},{"id":"https://openalex.org/C69075417","wikidata":"https://www.wikidata.org/wiki/Q515701","display_name":"Linked data","level":3,"score":0.303600013256073},{"id":"https://openalex.org/C49261128","wikidata":"https://www.wikidata.org/wiki/Q1132455","display_name":"Hazard","level":2,"score":0.2912999987602234},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.27059999108314514},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.26919999718666077},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.2660999894142151},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.26420000195503235},{"id":"https://openalex.org/C130440534","wikidata":"https://www.wikidata.org/wiki/Q14946528","display_name":"Conflation","level":2,"score":0.26339998841285706},{"id":"https://openalex.org/C159620131","wikidata":"https://www.wikidata.org/wiki/Q1938983","display_name":"Spatial analysis","level":2,"score":0.26179999113082886}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1145/3799682.3841078","doi":"https://doi.org/10.1145/3799682.3841078","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3799682.3841078","pdf_url":null,"source":{"id":"https://openalex.org/S4393918199","display_name":"ACM International Conference on Information and Knowledge Management (CIKM)","issn_l":"2155-0751","issn":["2155-0751"],"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"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 35th ACM International Conference on Information and Knowledge Management","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2608.22634","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2608.22634","pdf_url":"https://arxiv.org/pdf/2608.22634","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,"listed_in":[],"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"},{"id":"doi:10.48550/arxiv.2608.22634","doi":"https://doi.org/10.48550/arxiv.2608.22634","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2608.22634","pdf_url":null,"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,"listed_in":[],"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":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.1145/3799682.3841078","doi":"https://doi.org/10.1145/3799682.3841078","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3799682.3841078","pdf_url":null,"source":{"id":"https://openalex.org/S4393918199","display_name":"ACM International Conference on Information and Knowledge Management (CIKM)","issn_l":"2155-0751","issn":["2155-0751"],"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"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 35th ACM International Conference on Information and Knowledge Management","raw_type":"proceedings-article"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7204163897.pdf","grobid_xml":"https://content.openalex.org/works/W7204163897.grobid-xml"},"referenced_works_count":41,"referenced_works":["https://openalex.org/W2080133951","https://openalex.org/W2799089834","https://openalex.org/W3027879771","https://openalex.org/W3101045333","https://openalex.org/W3126662990","https://openalex.org/W3211686893","https://openalex.org/W4383046456","https://openalex.org/W4389519449","https://openalex.org/W4389520749","https://openalex.org/W4391045944","https://openalex.org/W4391801202","https://openalex.org/W4391988367","https://openalex.org/W4392822465","https://openalex.org/W4393089602","https://openalex.org/W4400531953","https://openalex.org/W4406157352","https://openalex.org/W4406880219","https://openalex.org/W4407308255","https://openalex.org/W4407953132","https://openalex.org/W4409380961","https://openalex.org/W4410297395","https://openalex.org/W4410486519","https://openalex.org/W4412874358","https://openalex.org/W4414462928","https://openalex.org/W4414566209","https://openalex.org/W4414921206","https://openalex.org/W4415352681","https://openalex.org/W4415797504","https://openalex.org/W4416035704","https://openalex.org/W4416063600","https://openalex.org/W4416178253","https://openalex.org/W4416354085","https://openalex.org/W4417511326","https://openalex.org/W6949549905","https://openalex.org/W7075994024","https://openalex.org/W7080222740","https://openalex.org/W7123836211","https://openalex.org/W7127046231","https://openalex.org/W7133224126","https://openalex.org/W7160376684","https://openalex.org/W7162291148"],"related_works":["https://openalex.org/W7150875577","https://openalex.org/W7204644703","https://openalex.org/W7130654464","https://openalex.org/W7118001266","https://openalex.org/W7117726295","https://openalex.org/W4409380961","https://openalex.org/W4417252285","https://openalex.org/W7077488675","https://openalex.org/W4415262817","https://openalex.org/W7127046231"],"abstract_inverted_index":{"Current":[0],"work":[1,170],"on":[2,128],"improving":[3],"reliability":[4,32],"in":[5,52,73,190],"large":[6],"language":[7],"model":[8],"(LLM)-":[9],"generated":[10],"answers":[11],"has":[12],"primarily":[13],"leveraged":[14],"Retrieval-Augmented":[15],"Generation":[16],"(RAG),":[17],"knowledge-graph":[18],"augmentation,":[19],"and":[20,30,36,159,184],"reinforcement":[21],"learning.":[22],"While":[23],"these":[24],"methods":[25],"are":[26],"adept":[27],"at":[28],"enhancing":[29],"measuring":[31],"through":[33,105],"semantic":[34,43,157],"similarity":[35,44,158],"faithfulness,":[37],"they":[38],"often":[39],"struggle":[40],"to":[41,79,150],"distinguish":[42],"from":[45],"geographic":[46,58,112,182],"validity.":[47],"This":[48,108,169],"is":[49,66],"especially":[50],"critical":[51],"natural":[53],"hazard":[54],"management":[55],"domains":[56],"where":[57],"granularity":[59],"(i.e.,":[60],"town":[61],"vs.":[62,64],"city":[63],"state)":[65],"significant":[67],"for":[68,121,144,155,187],"decision-making,":[69],"as":[70],"responses":[71],"valid":[72],"one":[74],"municipality":[75],"may":[76],"not":[77],"transfer":[78],"another.":[80],"In":[81],"such":[82],"domains,":[83],"a":[84,96,115,129,172],"confidently":[85],"wrong":[86],"answer":[87],"carries":[88],"greater":[89],"risk":[90],"than":[91],"abstaining.":[92],"We":[93],"present":[94],"GeoRisk-RAG,":[95],"novel":[97,130],"hierarchy-aware":[98],"framework":[99,109],"that":[100,137],"addresses":[101],"this":[102],"geographic-validity":[103],"gap":[104],"selective":[106],"answering.":[107],"explicitly":[110],"estimates":[111],"applicability":[113],"using":[114],"Directed":[116],"Acyclic":[117],"Graph":[118],"(DAG)-based":[119],"distance":[120],"context":[122],"retrieval":[123],"before":[124],"response":[125],"generation.":[126],"Experiments":[127],"held-out":[131],"wildfire-related":[132],"question-answering":[133],"(QA)":[134],"dataset":[135],"show":[136],"GeoRisk-RAG":[138],"significantly":[139],"reduces":[140],"false":[141],"confidence":[142],"rates":[143],"location-dependent":[145],"questions,":[146],"lowering":[147],"the":[148],"rate":[149],"0.009":[151],"compared":[152],"with":[153],"~0.090":[154],"standard":[156],"reranking":[160],"baselines,":[161],"while":[162],"consistently":[163],"achieving":[164],"higher":[165],"human":[166],"preference":[167],"alignment.":[168],"provides":[171],"more":[173],"comprehensive":[174],"assessment":[175],"of":[176],"end-to-end":[177],"RAG":[178],"pipelines":[179],"by":[180],"integrating":[181],"validity":[183],"selective-answering":[185],"behavior":[186],"safer":[188],"decision-making":[189],"geospatial":[191],"domains.":[192]},"counts_by_year":[],"updated_date":"2026-11-07T11:25:07.637180","created_date":"2026-08-26T00:00:00"}
