2 citations · 2 across the 4 of their papers we have counts for
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cs.CL2023★ 2 cited
Evaluating the Robustness to Instructions of Large Language Models
Yuansheng Ni, Sichao Jiang, Xinyu wu +2
Recently, Instruction fine-tuning has risen to prominence as a potential method for enhancing the zero-shot capabilities of Large Language Models (LLMs) on novel tasks. This techni…
cs.CL2023
Revisiting Automated Prompting: Are We Actually Doing Better?
Yulin Zhou, Yiren Zhao, Ilia Shumailov +2
Current literature demonstrates that Large Language Models (LLMs) are great few-shot learners, and prompting significantly increases their performance on a range of downstream task…