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