{"id":"https://openalex.org/W4372262691","doi":"https://doi.org/10.1109/icassp49357.2023.10096136","title":"Narrow Down Before Selection: A Dynamic Exclusion Model for Multiple-Choice QA","display_name":"Narrow Down Before Selection: A Dynamic Exclusion Model for Multiple-Choice QA","publication_year":2023,"publication_date":"2023-05-05","ids":{"openalex":"https://openalex.org/W4372262691","doi":"https://doi.org/10.1109/icassp49357.2023.10096136"},"language":"en","primary_location":{"id":"doi:10.1109/icassp49357.2023.10096136","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp49357.2023.10096136","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5077383364","display_name":"Xiyan Liu","orcid":"https://orcid.org/0000-0002-0102-9636"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xiyan Liu","raw_affiliation_strings":["Beijing University of Posts and Telecommunications,School of Artificial Intelligence,China","School of Artificial Intelligence, Beijing University of Posts and Telecommunications, China"],"affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications,School of Artificial Intelligence,China","institution_ids":["https://openalex.org/I139759216"]},{"raw_affiliation_string":"School of Artificial Intelligence, Beijing University of Posts and Telecommunications, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043294129","display_name":"Yidong Shi","orcid":null},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yidong Shi","raw_affiliation_strings":["Beijing University of Posts and Telecommunications,School of Artificial Intelligence,China","School of Artificial Intelligence, Beijing University of Posts and Telecommunications, China"],"affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications,School of Artificial Intelligence,China","institution_ids":["https://openalex.org/I139759216"]},{"raw_affiliation_string":"School of Artificial Intelligence, Beijing University of Posts and Telecommunications, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023135578","display_name":"Ruifang Liu","orcid":"https://orcid.org/0000-0003-1801-6759"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ruifang Liu","raw_affiliation_strings":["Beijing University of Posts and Telecommunications,School of Artificial Intelligence,China","School of Artificial Intelligence, Beijing University of Posts and Telecommunications, China"],"affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications,School of Artificial Intelligence,China","institution_ids":["https://openalex.org/I139759216"]},{"raw_affiliation_string":"School of Artificial Intelligence, Beijing University of Posts and Telecommunications, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068137955","display_name":"Ge Bai","orcid":null},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ge Bai","raw_affiliation_strings":["Beijing University of Posts and Telecommunications,School of Artificial Intelligence,China","School of Artificial Intelligence, Beijing University of Posts and Telecommunications, China"],"affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications,School of Artificial Intelligence,China","institution_ids":["https://openalex.org/I139759216"]},{"raw_affiliation_string":"School of Artificial Intelligence, Beijing University of Posts and Telecommunications, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5085130854","display_name":"Yanyi Chen","orcid":"https://orcid.org/0000-0002-9158-3824"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yanyi Chen","raw_affiliation_strings":["Beijing University of Posts and Telecommunications,School of Artificial Intelligence,China","School of Artificial Intelligence, Beijing University of Posts and Telecommunications, China"],"affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications,School of Artificial Intelligence,China","institution_ids":["https://openalex.org/I139759216"]},{"raw_affiliation_string":"School of Artificial Intelligence, Beijing University of Posts and Telecommunications, China","institution_ids":["https://openalex.org/I139759216"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5077383364"],"corresponding_institution_ids":["https://openalex.org/I139759216"],"apc_list":null,"apc_paid":null,"fwci":0.3497,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.63051913,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9998999834060669,"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":0.9998999834060669,"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/T13274","display_name":"Expert finding and Q&A systems","score":0.996999979019165,"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"}},{"id":"https://openalex.org/T12031","display_name":"Speech and dialogue systems","score":0.9824000000953674,"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":0.8693207502365112},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.7556077241897583},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.7416678071022034},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.7043565511703491},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.6587597131729126},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.502716064453125},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4312267303466797},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.06688180565834045},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.0617123544216156}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8693207502365112},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.7556077241897583},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.7416678071022034},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.7043565511703491},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.6587597131729126},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.502716064453125},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4312267303466797},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.06688180565834045},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0617123544216156},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp49357.2023.10096136","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp49357.2023.10096136","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.8100000023841858,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W2896457183","https://openalex.org/W2898695519","https://openalex.org/W2965373594","https://openalex.org/W2996428491","https://openalex.org/W2996848635","https://openalex.org/W2997561853","https://openalex.org/W2998579922","https://openalex.org/W3034838723","https://openalex.org/W3034987253","https://openalex.org/W3035260104","https://openalex.org/W3099655892","https://openalex.org/W3103984761","https://openalex.org/W3123091710","https://openalex.org/W4206674056","https://openalex.org/W4225377340","https://openalex.org/W4288089799","https://openalex.org/W4385245566","https://openalex.org/W6739901393","https://openalex.org/W6755207826","https://openalex.org/W6755829550","https://openalex.org/W6766673545","https://openalex.org/W6768021236","https://openalex.org/W6769627184","https://openalex.org/W6785635111"],"related_works":["https://openalex.org/W4390516098","https://openalex.org/W2181948922","https://openalex.org/W2384362569","https://openalex.org/W4205302943","https://openalex.org/W2119949815","https://openalex.org/W2561132942","https://openalex.org/W2142795561","https://openalex.org/W3155418658","https://openalex.org/W2389015757","https://openalex.org/W4386392971"],"abstract_inverted_index":{"Multiple-choice":[0],"question":[1],"answering":[2],"(MCQA)":[3],"is":[4,25],"a":[5,15,21,26,70],"challenging":[6],"task":[7],"that":[8],"requires":[9],"selecting":[10],"the":[11,40,44,56,61,92,106],"correct":[12],"answer":[13],"from":[14],"set":[16],"of":[17,58,63,108],"options":[18,89],"based":[19],"on":[20,39,100],"given":[22],"question.":[23],"There":[24],"trend":[27],"to":[28,33,47,90],"use":[29,57],"pre-trained":[30],"encoder-decoder":[31],"models":[32],"solve":[34],"MCQA.":[35,64],"Previous":[36],"works":[37,99],"concentrate":[38],"decoder":[41],"and":[42],"adopt":[43],"generated":[45],"text":[46],"enhance":[48],"model":[49,73],"performance.":[50],"However,":[51],"few":[52],"studies":[53],"have":[54],"optimized":[55],"encoders":[59],"for":[60,74],"characteristics":[62],"In":[65],"this":[66],"work,":[67],"we":[68],"propose":[69],"dynamic":[71],"exclusion":[72],"MCQA":[75,103],"named":[76],"ExcMC,":[77],"which":[78],"mimics":[79],"human":[80],"thinking":[81],"in":[82],"selection.":[83],"It":[84],"dynamically":[85],"eliminates":[86],"several":[87],"incorrect":[88],"optimize":[91],"encoder":[93],"usage.":[94],"ExcMC":[95],"outperforms":[96],"existing":[97],"comparable":[98],"two":[101],"widely-used":[102],"datasets,":[104],"demonstrating":[105],"effectiveness":[107],"our":[109],"model.":[110]},"counts_by_year":[{"year":2024,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
