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Text entry is an essential task in our day-to-day digital interactions.
Note on cohen’s kappa
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Large language models are zero-shot reasoners
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Augmentative and alternative communication (aac) advances: A review of configurations for individuals with a speech disability
Y. Elsahar, S. Hu, K. Bouazza-Marouf, D. Kerr, and A. Mansor · 2019
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Predicting next word using rnn and lstm cells: Stastical language modeling
A. F. Ganai and F. Khursheed · 2019
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How to fine-tune bert for text classification?
C. Sun, X. Qiu, Y. Xu, and X. Huang · 2019
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Words prediction based on n-gram model for free-text entry in electronic health records
A. Yazdani, R. Safdari, A. Golkar, and S. R. Niakan Kalhori · 2019
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Type, then correct: intelligent text correction techniques for mobile text entry using neural networks
M. R. Zhang, H. Wen, and J. O. Wobbrock · 2019
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Towards a human-like open-domain chatbot
D. Adiwardana, M.-T. Luong, D. R. So, J. Hall, N. Fiedel, G. Thoppil, Z. Yang, A. Kulshreshtha, G. Nemade, Y. Gao, et al · 2020
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Language models are few-shot learners
T. Brown, B. Mann, N. Ryder, M. Subbiah, J. D. Kaplan, P. Dhariwal, A. Neelakantan, P. Shyam, G. Sastry, A. Askell, et al · 2020
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X. Wang, J. Wei, D. Schuurmans, Q. Le, E. Chi, and D. Zhou · 2022
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Chain of thought prompting elicits reasoning in large language models
J. Wei, X. Wang, D. Schuurmans, M. Bosma, E. Chi, Q. Le, and D. Zhou · 2022
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Perd: Personalized emoji recommendation with dynamic user preference
X. Zheng, G. Zhao, L. Zhu, and X. Qian · 2022
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Least-to-most prompting enables complex reasoning in large language models
D. Zhou, N. Schärli, L. Hou, J. Wei, N. Scales, X. Wang, D. Schuurmans, O. Bousquet, Q. Le, and E. Chi · 2022
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Large language models are human-level prompt engineers
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Can large language models be an alternative to human evaluations?
C.-H. Chiang and H.-y. Lee · 2023
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Large language models are state-of-the-art evaluators of translation quality
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A prompt pattern catalog to enhance prompt engineering with chatgpt
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Tinkerable aac keyboard
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