{"id":"https://openalex.org/W4310608760","doi":"https://doi.org/10.1109/ialp57159.2022.9961244","title":"Paragraph-level Tibetan Question Generation for Machine Reading Comprehension","display_name":"Paragraph-level Tibetan Question Generation for Machine Reading Comprehension","publication_year":2022,"publication_date":"2022-10-27","ids":{"openalex":"https://openalex.org/W4310608760","doi":"https://doi.org/10.1109/ialp57159.2022.9961244"},"language":"en","primary_location":{"id":"doi:10.1109/ialp57159.2022.9961244","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ialp57159.2022.9961244","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 International Conference on Asian Language Processing (IALP)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5100644546","display_name":"Sisi Liu","orcid":"https://orcid.org/0000-0002-5582-4352"},"institutions":[{"id":"https://openalex.org/I145897649","display_name":"Minzu University of China","ror":"https://ror.org/0044e2g62","country_code":"CN","type":"education","lineage":["https://openalex.org/I145897649"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Sisi Liu","raw_affiliation_strings":["School of Information Engineering, Minzu University of China","National Language Resource Monitoring & Research Center Minority Languages Branch"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information Engineering, Minzu University of China","institution_ids":["https://openalex.org/I145897649"]},{"raw_affiliation_string":"National Language Resource Monitoring & Research Center Minority Languages Branch","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101627369","display_name":"Chaofan Chen","orcid":"https://orcid.org/0000-0002-9250-5887"},"institutions":[{"id":"https://openalex.org/I145897649","display_name":"Minzu University of China","ror":"https://ror.org/0044e2g62","country_code":"CN","type":"education","lineage":["https://openalex.org/I145897649"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chaofan Chen","raw_affiliation_strings":["School of Information Engineering, Minzu University of China","National Language Resource Monitoring & Research Center Minority Languages Branch"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information Engineering, Minzu University of China","institution_ids":["https://openalex.org/I145897649"]},{"raw_affiliation_string":"National Language Resource Monitoring & Research Center Minority Languages Branch","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101731298","display_name":"Yuan Sun","orcid":"https://orcid.org/0000-0003-0565-9659"},"institutions":[{"id":"https://openalex.org/I145897649","display_name":"Minzu University of China","ror":"https://ror.org/0044e2g62","country_code":"CN","type":"education","lineage":["https://openalex.org/I145897649"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuan Sun","raw_affiliation_strings":["School of Information Engineering, Minzu University of China","National Language Resource Monitoring & Research Center Minority Languages Branch"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information Engineering, Minzu University of China","institution_ids":["https://openalex.org/I145897649"]},{"raw_affiliation_string":"National Language Resource Monitoring & Research Center Minority Languages Branch","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I145897649"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"1","issue":null,"first_page":"280","last_page":"285"},"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/T10181","display_name":"Natural Language Processing Techniques","score":0.9980000257492065,"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":0.9847999811172485,"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/computer-science","display_name":"Computer science","score":0.8156218528747559},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.6811004877090454},{"id":"https://openalex.org/keywords/fluency","display_name":"Fluency","score":0.6674934029579163},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6545528173446655},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.6032114028930664},{"id":"https://openalex.org/keywords/paragraph","display_name":"Paragraph","score":0.6023592352867126},{"id":"https://openalex.org/keywords/comprehension","display_name":"Comprehension","score":0.5504091382026672},{"id":"https://openalex.org/keywords/reading","display_name":"Reading (process)","score":0.44645440578460693},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.4379728138446808},{"id":"https://openalex.org/keywords/reading-comprehension","display_name":"Reading comprehension","score":0.4363754987716675},{"id":"https://openalex.org/keywords/repetition","display_name":"Repetition (rhetorical device)","score":0.42680424451828003},{"id":"https://openalex.org/keywords/language-model","display_name":"Language model","score":0.4126669764518738},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.24935674667358398}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8156218528747559},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.6811004877090454},{"id":"https://openalex.org/C2777413886","wikidata":"https://www.wikidata.org/wiki/Q3276013","display_name":"Fluency","level":2,"score":0.6674934029579163},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6545528173446655},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.6032114028930664},{"id":"https://openalex.org/C2777206241","wikidata":"https://www.wikidata.org/wiki/Q194431","display_name":"Paragraph","level":2,"score":0.6023592352867126},{"id":"https://openalex.org/C511192102","wikidata":"https://www.wikidata.org/wiki/Q5156948","display_name":"Comprehension","level":2,"score":0.5504091382026672},{"id":"https://openalex.org/C554936623","wikidata":"https://www.wikidata.org/wiki/Q199657","display_name":"Reading (process)","level":2,"score":0.44645440578460693},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.4379728138446808},{"id":"https://openalex.org/C2778780117","wikidata":"https://www.wikidata.org/wiki/Q3269423","display_name":"Reading comprehension","level":3,"score":0.4363754987716675},{"id":"https://openalex.org/C2776141515","wikidata":"https://www.wikidata.org/wiki/Q1274479","display_name":"Repetition (rhetorical device)","level":2,"score":0.42680424451828003},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.4126669764518738},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.24935674667358398},{"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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ialp57159.2022.9961244","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ialp57159.2022.9961244","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 International Conference on Asian Language Processing (IALP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","score":0.7799999713897705,"display_name":"Quality Education"}],"awards":[{"id":"https://openalex.org/G5412369588","display_name":null,"funder_award_id":"2022QNYL33","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"}],"funders":[{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W1531374185","https://openalex.org/W2109609717","https://openalex.org/W2250571015","https://openalex.org/W2606333299","https://openalex.org/W2610891036","https://openalex.org/W2622069672","https://openalex.org/W2753613501","https://openalex.org/W2804292122","https://openalex.org/W2808074080","https://openalex.org/W2889670144","https://openalex.org/W2890166583","https://openalex.org/W2896457183","https://openalex.org/W2951534261","https://openalex.org/W2962717047","https://openalex.org/W2962977247","https://openalex.org/W2963250244","https://openalex.org/W2963339397","https://openalex.org/W2963748441","https://openalex.org/W2964165364","https://openalex.org/W2970705401","https://openalex.org/W2970796366","https://openalex.org/W2988673764","https://openalex.org/W6631875545","https://openalex.org/W6691989917","https://openalex.org/W6729938257","https://openalex.org/W6736830713","https://openalex.org/W6738894381","https://openalex.org/W6743492414","https://openalex.org/W6755207826"],"related_works":["https://openalex.org/W2377059580","https://openalex.org/W4200355488","https://openalex.org/W127000293","https://openalex.org/W3215892509","https://openalex.org/W2928616779","https://openalex.org/W2412592434","https://openalex.org/W2010523086","https://openalex.org/W4244602709","https://openalex.org/W594987446","https://openalex.org/W2052148722"],"abstract_inverted_index":{"The":[0,77,139,152],"question":[1,51,67,134,146,149,153,165],"generation":[2,52,68,135,147,154],"task":[3,49],"can":[4],"automatically":[5],"generate":[6,161],"large-scale":[7,36],"questions":[8,173],"to":[9,32,109,120,160],"provide":[10,110],"training":[11],"data":[12],"for":[13,23,113],"reading":[14,127],"comprehension":[15],"tasks":[16],"and":[17,38,45,56,85,148,163,185,205],"QA":[18],"systems,":[19],"which":[20],"are":[21],"crucial":[22],"low-resource":[24],"languages":[25],"such":[26],"as":[27],"Tibetan.":[28,94],"At":[29],"present,":[30],"due":[31],"the":[33,43,48,54,64,70,81,86,97,114,122,145,156,164,169,176,192,209,212],"emergence":[34],"of":[35,50,83,90,116,124,142,171,211],"datasets":[37,84,123],"pre-trained":[39,105],"language":[40,106],"models":[41,92],"in":[42,53,69,74,93],"Chinese":[44,55],"English":[46,57],"domains,":[47],"domains":[58],"has":[59,199],"been":[60],"well":[61],"developed,":[62],"while":[63],"research":[65],"on":[66],"Tibetan":[71,104,125,133],"is":[72,80],"still":[73],"its":[75],"infancy.":[76],"main":[78],"reason":[79],"lack":[82],"relatively":[87],"backward":[88],"development":[89,115],"various":[91,117],"To":[95],"solve":[96],"above":[98],"questions,":[99,162],"this":[100,129],"paper":[101,130],"constructs":[102],"a":[103,111,132],"model":[107,136,140,198],"TiBERT":[108],"basis":[112],"downstream":[118],"tasks,":[119],"expand":[121],"machine":[126],"comprehension,":[128],"proposes":[131],"named":[137],"TQGR.":[138],"consists":[141],"two":[143],"parts,":[144],"quality":[150,166,170],"assessment.":[151],"adopts":[155],"classic":[157],"seq2seq":[158],"architecture":[159],"assessment":[167],"improves":[168],"generated":[172],"by":[174],"evaluating":[175],"fluency":[177],"reward":[178,183],"score,":[179],"word":[180],"repetition":[181],"rate":[182],"score":[184],"interrogative":[186],"words":[187],"classification":[188],"auxiliary":[189],"task.":[190],"Finally,":[191],"experimental":[193],"results":[194],"show":[195],"that":[196],"our":[197],"higher":[200],"performance":[201],"than":[202],"baseline":[203],"models,":[204],"ablation":[206],"experiments":[207],"demonstrate":[208],"effectiveness":[210],"three":[213],"mechanism.":[214]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
