QARR-FSQA: Question-Answer Replacement and Removal Pretraining Framework for Few-Shot Question Answering

Journal Article · 01 January 2024 · IEEE Access

DOI: https://doi.org/10.1109/ACCESS.2024.3487581 · OSTI ID:2476269

Wah Tan, Siao  ^[1]; Poo Lee, Chin  ^[2]; Ming Lim, Kian  ^[3]; Tee, Connie  ^[1]; Alqahtani, Ali  ^[4]

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1. Faculty of Information Science and Technology, Multimedia University, Malacca, Malaysia
2. School of AI and Advanced Computing, Xi’,an Jiaotong-Liverpool University, Suzhou, Jiangsu, China
3. School of Computer Science, University of Nottingham Ningbo China, Yinzhou, Ningbo, Zhejiang, China
4. Department of Computer Science, King Khalid University, Abha, Saudi Arabia

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• Sponsoring Organization: USDOE Office of Electricity (OE), Advanced Grid Research & Development. Power Systems Engineering Research
• OSTI ID: 2476269
• Journal Information: IEEE Access, Journal Name: IEEE Access Vol. 12; ISSN 2169-3536
• Publisher: Institute of Electrical and Electronics EngineersCopyright Statement
• Country of Publication: United States
• Language: English