{"id":"https://openalex.org/W4378471480","doi":"https://doi.org/10.48550/arxiv.2305.14613","title":"Selectively Answering Ambiguous Questions","display_name":"Selectively Answering Ambiguous Questions","publication_year":2023,"publication_date":"2023-05-24","ids":{"openalex":"https://openalex.org/W4378471480","doi":"https://doi.org/10.48550/arxiv.2305.14613"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2305.14613","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2305.14613","pdf_url":"https://arxiv.org/pdf/2305.14613","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2305.14613","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5090951421","display_name":"Jeremy R. Cole","orcid":"https://orcid.org/0000-0001-7147-5888"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Cole, Jeremy R.","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030833444","display_name":"Michael J. Q. Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Michael J. Q.","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5110778504","display_name":"Daniel Gillick","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gillick, Daniel","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000738730","display_name":"Julian Martin Eisenschlos","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Eisenschlos, Julian Martin","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5055033421","display_name":"Bhuwan Dhingra","orcid":"https://orcid.org/0000-0002-6874-9515"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Dhingra, Bhuwan","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5047699861","display_name":"Jacob Eisenstein","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Eisenstein, Jacob","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5090951421"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9994999766349792,"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":0.9994999766349792,"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":0.9828000068664551,"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":0.9739999771118164,"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":0.8564642071723938},{"id":"https://openalex.org/keywords/perspective","display_name":"Perspective (graphical)","score":0.7265794277191162},{"id":"https://openalex.org/keywords/variety","display_name":"Variety (cybernetics)","score":0.6918351650238037},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6906232833862305},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.6179362535476685},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5919116735458374},{"id":"https://openalex.org/keywords/repetition","display_name":"Repetition (rhetorical device)","score":0.5513578653335571},{"id":"https://openalex.org/keywords/trustworthiness","display_name":"Trustworthiness","score":0.4342005252838135},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.43008118867874146},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3199388086795807},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.1705905795097351}],"concepts":[{"id":"https://openalex.org/C44291984","wikidata":"https://www.wikidata.org/wiki/Q1074173","display_name":"Question answering","level":2,"score":0.8564642071723938},{"id":"https://openalex.org/C12713177","wikidata":"https://www.wikidata.org/wiki/Q1900281","display_name":"Perspective (graphical)","level":2,"score":0.7265794277191162},{"id":"https://openalex.org/C136197465","wikidata":"https://www.wikidata.org/wiki/Q1729295","display_name":"Variety (cybernetics)","level":2,"score":0.6918351650238037},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6906232833862305},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.6179362535476685},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5919116735458374},{"id":"https://openalex.org/C2776141515","wikidata":"https://www.wikidata.org/wiki/Q1274479","display_name":"Repetition (rhetorical device)","level":2,"score":0.5513578653335571},{"id":"https://openalex.org/C153701036","wikidata":"https://www.wikidata.org/wiki/Q659974","display_name":"Trustworthiness","level":2,"score":0.4342005252838135},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.43008118867874146},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3199388086795807},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.1705905795097351},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2305.14613","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2305.14613","pdf_url":"https://arxiv.org/pdf/2305.14613","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},{"id":"doi:10.48550/arxiv.2305.14613","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2305.14613","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2305.14613","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2305.14613","pdf_url":"https://arxiv.org/pdf/2305.14613","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},"sustainable_development_goals":[{"display_name":"Quality Education","score":0.6899999976158142,"id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4378471480.pdf"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2384605597","https://openalex.org/W2996195527","https://openalex.org/W2387743295","https://openalex.org/W2978375718","https://openalex.org/W2612358220","https://openalex.org/W2351132524","https://openalex.org/W2916738897","https://openalex.org/W2115758952","https://openalex.org/W2392934913","https://openalex.org/W2003474770"],"abstract_inverted_index":{"Trustworthy":[0],"language":[1],"models":[2],"should":[3],"abstain":[4,114],"from":[5,73,89],"answering":[6,72,78],"questions":[7,82,93],"when":[8,112],"they":[9],"do":[10],"not":[11],"know":[12],"the":[13,16,34,38,43,51,64,106,124,139],"answer.":[14],"However,":[15],"answer":[17,44,52],"to":[18,53,61,110,113,137,164],"a":[19,25,54,79,84,90],"question":[20,39,55,71],"can":[21,56],"be":[22,58,138],"unknown":[23],"for":[24],"variety":[26],"of":[27,63,81,87,92,144],"reasons.":[28],"Prior":[29],"research":[30],"has":[31],"focused":[32],"on":[33,77,172],"case":[35,140],"in":[36,94,131],"which":[37,95],"is":[40,45],"clear":[41],"and":[42,146],"unambiguous":[46,166],"but":[47,50],"possibly":[48],"unknown,":[49],"also":[57],"unclear":[59],"due":[60],"uncertainty":[62,145],"questioner's":[65],"intent":[66],"or":[67,127,150],"context.":[68],"We":[69,134],"investigate":[70],"this":[74,101,136],"perspective,":[75],"focusing":[76],"subset":[80],"with":[83,149,168],"high":[85],"degree":[86],"accuracy,":[88],"set":[91],"many":[96],"are":[97],"inherently":[98],"ambiguous.":[99],"In":[100],"setting,":[102],"we":[103],"find":[104,135],"that":[105,157],"most":[107],"reliable":[108],"approach":[109],"decide":[111],"involves":[115],"quantifying":[116],"repetition":[117],"within":[118],"sampled":[119],"model":[120,147],"outputs,":[121],"rather":[122],"than":[123],"model's":[125],"likelihood":[126],"self-verification":[128],"as":[129],"used":[130],"prior":[132],"work.":[133],"across":[141],"different":[142],"types":[143],"scales,and":[148],"without":[151],"instruction":[152],"tuning.":[153],"Our":[154],"results":[155],"suggest":[156],"sampling-based":[158],"confidence":[159],"scores":[160],"help":[161],"calibrate":[162],"answers":[163],"relatively":[165],"questions,":[167],"more":[169],"dramatic":[170],"improvements":[171],"ambiguous":[173],"questions.":[174]},"counts_by_year":[],"updated_date":"2026-03-11T14:59:36.786465","created_date":"2025-10-10T00:00:00"}