This is a graduate-level research course on Transformer and Large Language Models. Over the duration of this course, we will delve into the latest publications within the expansive domain of Large Language Models (LLMs), intelligent agents, and multimodal learning. Each student is entrusted with the following responsibilities: Conducting critical analyses and authoring paper reviews, programming with LLMs, delivering comprehensive paper presentations, and undertaking a substantial, research-quality course project. The intent behind this course is to foster a deep understanding of LLMs and their pivotal role in today's technological landscape.
Prerequisites: Neural network building experience or successfully finished a deep learning course.
Once the quarter starts, instructor approval is required to maintain enrollment in the course, including if students do not have the listed pre-requisite courses completed.