{"id":"https://openalex.org/W7147217111","doi":"https://doi.org/10.1109/cnml68938.2026.11453070","title":"Are you really satisfied with the completeness and conciseness of the explanations provided by the large language model?","display_name":"Are you really satisfied with the completeness and conciseness of the explanations provided by the large language model?","publication_year":2026,"publication_date":"2026-01-30","ids":{"openalex":"https://openalex.org/W7147217111","doi":"https://doi.org/10.1109/cnml68938.2026.11453070"},"language":null,"primary_location":{"id":"doi:10.1109/cnml68938.2026.11453070","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cnml68938.2026.11453070","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2026 International Conference on Communication Networks and Machine Learning (CNML)","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/A5132584357","display_name":"Junda Zhu","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Junda Zhu","raw_affiliation_strings":["Academy of Military Science,National Innovation Institute of Defense Technology,Beijing,China"],"affiliations":[{"raw_affiliation_string":"Academy of Military Science,National Innovation Institute of Defense Technology,Beijing,China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5132603836","display_name":"Guang Kou","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Guang Kou","raw_affiliation_strings":["Academy of Military Science,National Innovation Institute of Defense Technology,Beijing,China"],"affiliations":[{"raw_affiliation_string":"Academy of Military Science,National Innovation Institute of Defense Technology,Beijing,China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5068480085","display_name":"Zhenyu Wan","orcid":"https://orcid.org/0000-0002-0069-1951"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhenyu Wan","raw_affiliation_strings":["Academy of Military Science,National Innovation Institute of Defense Technology,Beijing,China"],"affiliations":[{"raw_affiliation_string":"Academy of Military Science,National Innovation Institute of Defense Technology,Beijing,China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5132584357"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.93886548,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1307","last_page":"1313"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.555400013923645,"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/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.555400013923645,"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/T11636","display_name":"Artificial Intelligence in Healthcare and Education","score":0.094200000166893,"subfield":{"id":"https://openalex.org/subfields/2718","display_name":"Health Informatics"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T11714","display_name":"Multimodal Machine Learning Applications","score":0.07919999957084656,"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/completeness","display_name":"Completeness (order theory)","score":0.8888999819755554},{"id":"https://openalex.org/keywords/suite","display_name":"Suite","score":0.6123999953269958},{"id":"https://openalex.org/keywords/mainstream","display_name":"Mainstream","score":0.545199990272522},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.44859999418258667},{"id":"https://openalex.org/keywords/readability","display_name":"Readability","score":0.31769999861717224}],"concepts":[{"id":"https://openalex.org/C17231256","wikidata":"https://www.wikidata.org/wiki/Q5156540","display_name":"Completeness (order theory)","level":2,"score":0.8888999819755554},{"id":"https://openalex.org/C79581498","wikidata":"https://www.wikidata.org/wiki/Q1367530","display_name":"Suite","level":2,"score":0.6123999953269958},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5978999733924866},{"id":"https://openalex.org/C2777617010","wikidata":"https://www.wikidata.org/wiki/Q18957","display_name":"Mainstream","level":2,"score":0.545199990272522},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.44859999418258667},{"id":"https://openalex.org/C539667460","wikidata":"https://www.wikidata.org/wiki/Q2414942","display_name":"Management science","level":1,"score":0.3806999921798706},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3424000144004822},{"id":"https://openalex.org/C2778143727","wikidata":"https://www.wikidata.org/wiki/Q1820650","display_name":"Readability","level":2,"score":0.31769999861717224},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.2700999975204468},{"id":"https://openalex.org/C195324797","wikidata":"https://www.wikidata.org/wiki/Q33742","display_name":"Natural language","level":2,"score":0.2590000033378601}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cnml68938.2026.11453070","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cnml68938.2026.11453070","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2026 International Conference on Communication Networks and Machine Learning (CNML)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4","score":0.7091325521469116}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":8,"referenced_works":["https://openalex.org/W2962833140","https://openalex.org/W2963961878","https://openalex.org/W3033639770","https://openalex.org/W3161820423","https://openalex.org/W3173805051","https://openalex.org/W3175591618","https://openalex.org/W3212606841","https://openalex.org/W4205870266"],"related_works":[],"abstract_inverted_index":{"Today,":[0],"large":[1,101],"language":[2,102],"models":[3],"(LLMs)":[4],"are":[5],"widely":[6],"regarded":[7],"as":[8,104],"assistants":[9],"for":[10],"solving":[11],"daily":[12],"problems.":[13],"Yet,":[14],"a":[15,38,52,88,100,105],"critical":[16],"question":[17],"persists:":[18],"\"Can":[19],"the":[20,32,44,56,78],"explanations":[21,36,60,83],"provided":[22],"by":[23,85],"LLMs":[24,116],"truly":[25],"satisfy":[26],"users?\"":[27],"How":[28],"to":[29,54,76,95,107],"scientifically":[30],"evaluate":[31,96],"quality":[33,57],"of":[34,47,58,82,122],"LLM":[35,59],"is":[37],"worthwhile":[39],"research":[40],"issue.":[41],"Starting":[42],"from":[43,61],"fundamental":[45],"concept":[46],"\"reasoning":[48],"explanations,\"":[49],"we":[50,92],"propose":[51],"method":[53],"assess":[55,77],"two":[62],"dimensions:":[63],"completeness":[64,79,124],"and":[65,80],"conciseness.":[66,130],"This":[67],"paper":[68],"introduces":[69],"QEBench,":[70],"an":[71],"automated":[72],"evaluation":[73],"suite":[74],"designed":[75],"conciseness":[81],"generated":[84],"LLMs.":[86],"Using":[87],"zero-shot,":[89],"prompt-free":[90],"approach,":[91],"applied":[93],"QEBench":[94],"mainstream":[97],"LLMs,":[98],"employing":[99],"model":[103],"judge":[106],"obtain":[108],"assessment":[109],"results.":[110],"Experimental":[111],"findings":[112],"indicate":[113],"that":[114],"current":[115],"meet":[117],"basic":[118],"requirements":[119],"in":[120,129],"terms":[121],"explanation":[123],"but":[125],"still":[126],"require":[127],"improvement":[128]},"counts_by_year":[],"updated_date":"2026-04-02T13:53:19.096889","created_date":"2026-04-02T00:00:00"}