28 citations · 96 across the 17 of their papers we have counts for
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cs.CL2023★ 4 cited
InfoPrompt: Information-Theoretic Soft Prompt Tuning for Natural Language Understanding
Junda Wu, Tong Yu, Rui Wang +6
Soft prompt tuning achieves superior performances across a wide range of few-shot tasks. However, the performances of prompt tuning can be highly sensitive to the initialization of…
cs.CL2023★ 5 cited
A Mathematical Abstraction for Balancing the Trade-off Between Creativity and Reality in Large Language Models
Ritwik Sinha, Zhao Song, Tianyi Zhou
Large Language Models have become popular for their remarkable capabilities in human-oriented tasks and traditional natural language processing tasks. Its efficient functioning is…
cs.CL2023★ 2 cited
The Closeness of In-Context Learning and Weight Shifting for Softmax Regression
Shuai Li, Zhao Song, Yu Xia +2
Large language models (LLMs) are known for their exceptional performance in natural language processing, making them highly effective in many human life-related or even job-related…