Safety of Large Language Models

Date2025-04-16 ~ 2025-04-25

Schedule

Introduction

This course introduces students to the core principles and challenges surrounding large-scale neural language models' safe and responsible development. It is designed for graduate students and technical professionals with prior experience in machine learning and natural language processing.

The course will explore the basics of LLMs, including architectural foundations, training procedures. The second part of the course goes deeper with exploring vulnerabilities such as hallucinations and adversarial attacks, and recent advances in aligning LLMs with human intent and values.

List of Lectures

1. Introduction to Transformer Models and LLMs

2. Training of LLMs: From Pretraining to Fine-tuning

3. Hallucination Detection in LLMs

4. Adversarial Attacks on Language Models

5. Alternatives to Transformers: LLMs and State-space models

Lecturer Intro

Alexey Zaytsev has deep expertise in machine learning and processing of sequential data. He publishes at top venues, including KDD, ACM Multimedia and AISTATS. Industrial applications of his results are now in service at companies Airbus, Porsche and Saudi Aramco among others.