Unit 4: Alignment and current research
In this unit, you will learn more about the alignment stage of LLM training. You will also see several examples of current research in this and related areas. The unit features both lecture-style reviews of recent developments and videos from research presentations.
Lectures
The lectures start by exploring LLMs alignment. You will then learn about current research on how LLMs store facts, efficient fine-tuning techniques, retrieval-augmented generation, and how tokenisation relates to LLM privacy and security. The series concludes by reflecting on the “stochastic parrots” debate.
| Section | Title | Video | Slides | Quiz |
|---|---|---|---|---|
| 4.1 | LLM alignment | video | slides | quiz |
| 4.2 | LLMs for fact completion | video | slides | quiz |
| 4.3 | Efficient fine-tuning | video | paper | quiz |
| 4.4 | Retrieval-augmented generation (until 17:50) | video | none | quiz |
| 4.5 | Adversarial tokenization | video | slides | quiz |
| 4.6 | LLMs as stochastic parrots (until 15:00) | video | none | quiz |
ImportantQuiz deadline
To earn a wildcard for this unit, you must complete the quizzes before the teaching session on Unit 4.
Lab
TBA