Deep Learning Reading Group
This is seventh session of 2024. We'll be discussing:
(Theory) An Explanation of In-Context Learning as Implicit Bayesian Inference (https://arxiv.org/abs/2111.02080):
- Large language models can perform in-context learning, where the model itself can learn at inference time to accomplish a downstream task specified only using a prompt. This paper provides one explanation for this phenomenon using ideas from Bayesian statistics. See also the blog post: https://www.inference.vc/implicit-bayesian-inference-in-sequence-models/
Upcoming material is to be read before each session, so that it may be discussed in an open format. Staff and students from all backgrounds who are interested in these topics are welcome. If you are interested but haven't been to a session yet, come along. There is no need to have participated in all sessions.