CS762 Fall 2023

Tentative Schedule (Subject to Change)

Week	Date	Topic	Reading materials	Assignments
1	Thursday, September 7	Course overview and introduction		Sign up for paper presentations and scribes (link to Google sheet)
2	Tuesday, September 12	Evolution of Neural Architecture (lecture)	D2L Book Chapter 7 & 10
2	Thursday, September 14	Evolution of Neural Architecture II	LLM architectures Attention Is All You Need (deep dive) BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer
3	Tuesday, September 19	Evolution of Neural Architecture III	LLM architectures Attention Is All You Need BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer (deep dive)
3	Thursday, September 21	Evolution of Neural Architecture IV	Vision Transformers An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale Hierarchical Vision Transformer using Shifted Windows End-to-End Object Detection with Transformers HOW DO VISION TRANSFORMERS WORK? (deep dive)
4	Tuesday, September 26	AI Safety and Alignment (lecture)		Team registration (link to Google sheet)
4	Thursday, September 28	AI Safety and Alignment II	Distributional shift in the wild Energy-based Out-of-distribution Detection How to Exploit Hyperspherical Embeddings for Out-of-Distribution Detection? Training OOD Detectors in their Natural Habitats Feed Two Birds with One Scone: Exploiting Wild Data for Both Out-of-Distribution Generalization and Detection (deep dive)
5	Tuesday, October 3	No class (use the time to discuss the project proposal with team)		Project proposal submission deadline on October 7 Midnight (download proposal latex template here)
5	Thursday, October 5	AI Safety and Alignment III	Alignment problem (method) Fine-Tuning Language Models from Human Preferences Training Language Models to Follow Instructions with Human Feedback(deep dive) Constitutional AI: Harmlessness from AI Feedback Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback Preference Ranking Optimization for Human Alignment
6	Tuesday, October 10	Meetings with Instructor to Review Project Proposals (optional)
6	Thursday, October 12	AI Safety and Alignment IV (no class, self-reading session)	Alignment problem (challenges and limitations) Red Teaming Language Models to Reduce Harms: Methods, Scaling Behaviors, and Lessons Learned Scaling Laws for Reward Model Overoptimization Fundamental Limitations of Alignment in LLMs Open Problems and Fundamental Limitations of Reinforcement Learning from Human Feedback (self read)
7	Tuesday, October 17	AI Safety and Alignment IV	Jailbreaks Universal and Transferable Adversarial Attacks on Aligned Language Models (deep dive) Jailbroken: How Does LLM Safety Training Fail?
7	Thursday, October 19	Interpretable Deep Learning I (lecture)
8	Tuesday, October 24	Interpretable Deep Learning II	Learning Deep Features for Discriminative Localization Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization "Why Should I Trust You?": Explaining the Predictions of Any Classifier Locating and Editing Factual Associations in GPT (deep dive) Mass Editing Memory in a Transformer
8	Thursday, October 26	Foundation models I (Lecture)
9	Tuesday, October 31	Foundation Models II	Large-scale pre-training Exploring the Limits of Weakly Supervised Pretraining Learning Transferable Visual Models From Natural Language Supervision Exploring the Limits of Large Scale Pre-training LLaMA: Open and Efficient Foundation Language Models Llama 2: Open Foundation and Fine-Tuned Chat Models (deep dive)
9	Thursday, Novermber 2	Foundation Models III	Emergent behaviors Scaling Laws for Neural Language Models Chain of Thought Prompting Elicits Reasoning in Large Language Models An Explanation of In-Context Learning as Implicit Bayesian Inference (deep dive) Rethinking the Role of Demonstrations: What Makes In-Context Learning Work?
10	Tuesday, Novermber 7	Foundation Models III	Parameter efficient adaptation LoRA: Low-Rank Adaptation of Large Language Models (deep dive) Prefix-Tuning: Optimizing Continuous Prompts for Generation The Power of Scale for Parameter-Efficient Prompt Tuning Learning to Prompt for Vision-Language Models
10	Thursday, November 9	Continual / Lifelong Learning I (Lecture)
11	Tuesday, November 14	Continual / Lifelong Learning II	LwF-Learning without Forgetting iCaRL - Incremental Classifier and Representation Learning Overcoming catastrophic forgetting in neural networks Dark Experience for General Continual Learning: a Strong, Simple Baseline Flattening Sharpness for Dynamic Gradient Projection Memory Benefits Continual Learning (deep dive)
11	Thursday, November 16	Deep Generative Model I (Lecture)	Goodfellow-Bengio-Courville Chapter 20
12	Tuesday, November 21	Deep Generative Model II	Foundations Denoising Diffusion Probabilistic Models (deep dive) Deep unsupervised learning using nonequilibrium thermodynamics Generative modeling by estimating gradients of the data distribution Improved techniques for training score-based generative models
12	Thursday, November 23	No class (Thanksgiving)
13	Tuesday, November 28	Deep Generative Model III	Applications High-Resolution Image Synthesis with Latent Diffusion Models (deep dive) Hierarchical Text-Conditional Image Generation with CLIP Latents Photorealistic Text-to-Image Diffusion Models with Deep Language Understanding
14	Tuesday, December 5	Final project presentation (Part I)
14	Tuesday, December 7	Final project presentation (Part II)
	Monday, December 18	Final project written report due (by end of the day)