Sean Welleck
https://wellecks.com/
CMU Advanced NLP Fall 2025 (22): Test-Time Scaling Strategies
CMU Advanced NLP Fall 2025 (21): Mixture of Experts
CMU Advanced NLP Fall 2025 (20): Long Sequence Models
CMU Advanced NLP Fall 2025 (19): Quantization
CMU Advanced NLP Fall 2025 (18): Parallelism and Distributed Training
CMU Advanced NLP Fall 2025 (17): Agents and RL
CMU Advanced NLP Fall 2025 (16): Reinforcement Learning for LLMs
CMU Advanced NLP Fall 2025 (15): Reinforcement Learning Fundamentals
CMU Advanced NLP Fall 2025 (14): Research Skills and Experimental Design
CMU Advanced NLP Fall 2025 (13): Evaluation and Benchmarks
CMU Advanced NLP Fall 2025 (12): Multimodal Modeling II
CMU Advanced NLP Fall 2025 (11): Multimodal Modeling I
CMU Advanced NLP Fall 2025 (10): Akari Asai - Retrieval and RAG
CMU Advanced NLP Fall 2025 (9): Decoding Algorithms
CMU Advanced NLP Fall 2025 (8): Fine-Tuning and Distillation
CMU Advanced NLP Fall 2025 (7): In-Context Learning and Prompting
CMU Advanced NLP Fall 2025 (6): Pretraining
CMU Advanced NLP Fall 2025 (5): Attention and Transformers
CMU Advanced NLP Fall 2025 (4): Recurrent Neural Networks
CMU Advanced NLP Fall 2025 (3): Language Modeling Fundamentals
CMU Advanced NLP Fall 2025 (2): Learned Representations
CMU Advanced NLP Fall 2025 (1): Introduction & Fundamentals
CMU Advanced NLP Spring 2025 (23): Multimodal Modeling II
CMU Advanced NLP Spring 2025 (22): AI for Mathematics
CMU Advanced NLP Spring 2025 (21): Multimodal Modeling I
CMU Advanced NLP Spring 2025 (20): Advanced Post-Training
CMU Advanced NLP Spring 2025 (19): Efficient Inference
CMU Advanced NLP Spring 2025 (18): Advanced Inference Strategies
CMU Advanced NLP Spring 2025 (17): Long-Context Models
CMU Advanced NLP Spring 2025 (16): Parallelism and Scaling