{"id":"https://openalex.org/W7161143934","doi":"https://doi.org/10.1109/access.2026.3693277","title":"Efficient Unified Framework for Difficulty-Controllable Question Generation: Large Language Models Enabling Active Learning Labeling and Prompt-Based Low-Rank Adaptation","display_name":"Efficient Unified Framework for Difficulty-Controllable Question Generation: Large Language Models Enabling Active Learning Labeling and Prompt-Based Low-Rank Adaptation","publication_year":2026,"publication_date":"2026-01-01","ids":{"openalex":"https://openalex.org/W7161143934","doi":"https://doi.org/10.1109/access.2026.3693277"},"language":"en","primary_location":{"id":"doi:10.1109/access.2026.3693277","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2026.3693277","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1109/access.2026.3693277","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100748281","display_name":"Xiaohui Dong","orcid":"https://orcid.org/0000-0002-9228-8552"},"institutions":[{"id":"https://openalex.org/I68986083","display_name":"Northwest Normal University","ror":"https://ror.org/00gx3j908","country_code":"CN","type":"education","lineage":["https://openalex.org/I68986083"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaohui Dong","raw_affiliation_strings":["College of Computer Science and Engineering, Northwest Normal University, Lanzhou, China"],"raw_orcid":"https://orcid.org/0000-0002-9228-8552","affiliations":[{"raw_affiliation_string":"College of Computer Science and Engineering, Northwest Normal University, Lanzhou, China","institution_ids":["https://openalex.org/I68986083"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5054606394","display_name":"Zhenyu Li","orcid":"https://orcid.org/0009-0002-6657-9986"},"institutions":[{"id":"https://openalex.org/I68986083","display_name":"Northwest Normal University","ror":"https://ror.org/00gx3j908","country_code":"CN","type":"education","lineage":["https://openalex.org/I68986083"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhengluo Li","raw_affiliation_strings":["College of Computer Science and Engineering, Northwest Normal University, Lanzhou, China"],"raw_orcid":"https://orcid.org/0009-0009-4456-8064","affiliations":[{"raw_affiliation_string":"College of Computer Science and Engineering, Northwest Normal University, Lanzhou, China","institution_ids":["https://openalex.org/I68986083"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I68986083"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.68320559,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"14","issue":null,"first_page":"76358","last_page":"76371"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.38920000195503235,"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":0.38920000195503235,"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/T12072","display_name":"Machine Learning and Algorithms","score":0.11919999867677689,"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/T11902","display_name":"Intelligent Tutoring Systems and Adaptive Learning","score":0.10779999941587448,"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/adaptation","display_name":"Adaptation (eye)","score":0.6215000152587891},{"id":"https://openalex.org/keywords/active-learning","display_name":"Active learning (machine learning)","score":0.5892999768257141},{"id":"https://openalex.org/keywords/domain-adaptation","display_name":"Domain adaptation","score":0.36730000376701355},{"id":"https://openalex.org/keywords/language-model","display_name":"Language model","score":0.35690000653266907},{"id":"https://openalex.org/keywords/perspective","display_name":"Perspective (graphical)","score":0.2924000024795532}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.855400025844574},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.6215000152587891},{"id":"https://openalex.org/C77967617","wikidata":"https://www.wikidata.org/wiki/Q4677561","display_name":"Active learning (machine learning)","level":2,"score":0.5892999768257141},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5519999861717224},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.37529999017715454},{"id":"https://openalex.org/C2776434776","wikidata":"https://www.wikidata.org/wiki/Q19246213","display_name":"Domain adaptation","level":3,"score":0.36730000376701355},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.35749998688697815},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.35690000653266907},{"id":"https://openalex.org/C12713177","wikidata":"https://www.wikidata.org/wiki/Q1900281","display_name":"Perspective (graphical)","level":2,"score":0.2924000024795532},{"id":"https://openalex.org/C183322885","wikidata":"https://www.wikidata.org/wiki/Q17007702","display_name":"Context model","level":3,"score":0.2741999924182892},{"id":"https://openalex.org/C2983448237","wikidata":"https://www.wikidata.org/wiki/Q1078276","display_name":"Language understanding","level":2,"score":0.260699987411499},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.25999999046325684}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2026.3693277","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2026.3693277","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:a9f79ddaac6f47619d19d6e393d6f08a","is_oa":true,"landing_page_url":"https://doaj.org/article/a9f79ddaac6f47619d19d6e393d6f08a","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 14, Pp 76358-76371 (2026)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2026.3693277","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2026.3693277","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2941869638","display_name":null,"funder_award_id":"62567006","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6573322868","display_name":null,"funder_award_id":"24YJA880007","funder_id":"https://openalex.org/F4320314366","funder_display_name":"Federation for the Humanities and Social Sciences"}],"funders":[{"id":"https://openalex.org/F4320314366","display_name":"Federation for the Humanities and Social Sciences","ror":"https://ror.org/00y8ab321"},{"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":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"The":[0],"task":[1],"of":[2,11,19,32,48,142,149,172],"Difficulty-Controllable":[3,52,119,198],"Question":[4],"Generation":[5],"(QG)":[6],"in":[7,43,186],"reading":[8],"comprehension":[9],"is":[10],"great":[12],"significance":[13],"for":[14,81,197],"improving":[15],"the":[16,44,118,126,129,157,160],"educational":[17],"applicability":[18,47],"automatically":[20],"generated":[21,49],"questions.":[22],"However,":[23],"existing":[24],"research":[25],"faces":[26],"two":[27],"core":[28],"challenges:":[29],"1)":[30],"lack":[31],"unified":[33,79,195],"difficulty":[34,90,106,135,188],"quantification":[35],"standards":[36],"and":[37,46,69,84,108,113,177],"annotated":[38],"datasets":[39],"leads":[40],"to":[41,66,103,115,117],"limitations":[42],"quality":[45],"questions;":[50],"2)":[51],"generation":[53],"relies":[54],"on":[55,93,125],"a":[56,78,134,146,194],"single":[57],"feature":[58],"or":[59],"high-cost":[60],"simulation":[61],"systems,":[62],"making":[63],"it":[64],"difficult":[65],"balance":[67],"diversity":[68],"practicality.":[70],"To":[71],"address":[72],"these":[73],"issues,":[74],"we":[75],"propose":[76],"DL-CQG,":[77],"framework":[80,88,131,192],"Difficulty":[82],"Labeling":[83],"Controllable":[85],"QG.":[86],"This":[87],"defines":[89],"levels":[91],"based":[92],"Bloom\u2019s":[94],"theory,":[95],"employs":[96],"Large":[97],"Language":[98],"Model-Augmented":[99],"Active":[100],"Learning":[101],"(LLM-AAL)":[102],"achieve":[104],"efficient":[105],"annotation,":[107],"fine-tuning":[109],"LLMs":[110],"with":[111,138,181],"prompts":[112],"LoRa":[114],"adapt":[116],"QG":[120,158,199],"task.":[121],"Experiments":[122],"show":[123],"that":[124],"EQG-RACE":[127],"dataset,":[128],"LLM-AAL":[130],"can":[132],"train":[133],"evaluation":[136],"model":[137,163],"an":[139,182],"accurate":[140],"rate":[141,185],"0.85,":[143],"using":[144],"only":[145],"small":[147],"number":[148],"samples,":[150],"which":[151],"significantly":[152],"reduces":[153],"annotation":[154],"costs.":[155],"In":[156],"task,":[159],"adapted":[161],"Llama-3.2-3B-Instruct":[162],"outperformed":[164],"all":[165],"baseline":[166],"methods":[167],"across":[168],"metrics,":[169],"achieving":[170],"scores":[171],"45.20":[173],"(BLEU-4),":[174],"50.01":[175],"(ROUGE-L),":[176],"81.26":[178],"(BERT":[179],"Score),":[180],"0.824":[183],"accuracy":[184],"question":[187],"control.":[189],"Our":[190],"proposed":[191],"establishes":[193],"paradigm":[196],"under":[200],"low-resource":[201],"conditions.":[202]},"counts_by_year":[],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2026-05-15T00:00:00"}