Title | XNLI: Explaining and Diagnosing NLI-based Visual Data Analysis |
Author | |
Publication Years | 2023
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DOI | |
Source Title | |
ISSN | 2160-9306
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Volume | PPIssue:99Pages:1-14 |
Keywords | |
URL | [Source Record] |
SUSTech Authorship | Others
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Data Source | IEEE
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PDF url | https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10026499 |
Citation statistics |
Cited Times [WOS]:0
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Document Type | Journal Article |
Identifier | http://kc.sustech.edu.cn/handle/2SGJ60CL/426991 |
Department | Department of Computer Science and Engineering |
Affiliation | 1.The State Key Lab of CAD & CG, Zhejiang University, Hangzhou, Zhejiang, China 2.Hong Kong University of Science and Technology, Hong Kong, China 3.MIT Media Lab, Cambridge, MA, USA 4.Department of Computer Science and Engineering, Southern University of Science and Technology, Guangdong, China 5.Laboratory of Art and Archaeology Image (Zhejiang University), Ministry of Education, China |
Recommended Citation GB/T 7714 |
Yingchaojie Feng,Xingbo Wang,Bo Pan,et al. XNLI: Explaining and Diagnosing NLI-based Visual Data Analysis[J]. IEEE Transactions on Visualization and Computer Graphics,2023,PP(99):1-14.
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APA |
Yingchaojie Feng.,Xingbo Wang.,Bo Pan.,Kam Kwai Wong.,Yi Ren.,...&Wei Chen.(2023).XNLI: Explaining and Diagnosing NLI-based Visual Data Analysis.IEEE Transactions on Visualization and Computer Graphics,PP(99),1-14.
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MLA |
Yingchaojie Feng,et al."XNLI: Explaining and Diagnosing NLI-based Visual Data Analysis".IEEE Transactions on Visualization and Computer Graphics PP.99(2023):1-14.
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