Want to create an interactive transcript for this episode?
Podcast: Arxiv Papers
Episode: Understanding Prompt Tuning and In-Context Learning via Meta-Learning height2pt
Description: The paper explores optimal prompting through a Bayesian perspective, highlighting limitations and advantages of prompt optimization methods, supported by experiments on LSTMs and Transformers.https://arxiv.org/abs//2505.17010YouTube: https://www.youtube.com/@ArxivPapersTikTok: https://www.tiktok.com/@arxiv_papersApple Podcasts: https://podcasts.apple.com/us/podcast/arxiv-papers/id1692476016Spotify: https://podcasters.spotify.com/pod/show/arxiv-papers