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CMU Advanced NLP Fall 2024 (1): Introduction to NLP
CMU Advanced NLP Fall 2024 (2): Representing Words
CMU Advanced NLP Fall 2024 (3): Language and Sequence Modeling
CMU Advanced NLP Fall 2024 (4): Attention and Transformers
CMU Advanced NLP Fall 2024 (5): Pre-training and Pre-trained Models
CMU Advanced NLP Fall 2024 (6): Instruction Tuning
CMU Advanced NLP Fall 2024 (7): Prompting and Complex Reasoning
CMU Advanced NLP Fall 2024 (8): Reinforcement Learning and Human Feedback
CMU Advanced NLP Fall 2024 (9): Experimental Design and Data Annotation
CMU Advanced NLP Fall 2024 (10): Retrieval and RAG
CMU Advanced NLP Fall 2024 (11): Distillation, Quantization, and Pruning
CMU Advanced NLP Fall 2024 (12): Domain Specific Modeling: Code and Math
CMU Advanced NLP Fall 2024 (13): Long Sequence Models
CMU Advanced NLP Fall 2024 (14): Ensembling and Mixture of Experts
CMU Advanced NLP Fall 2024 (15): Tool Use and LLM Agent Basics
CMU Advanced NLP Fall 2024 (16): Agents for Software Development and Web Browsing
CMU Advanced NLP Fall 2024 (17): Evaluation and Multimodal
CMU Advanced NLP Fall 2024 (18): Linguistics and Computational Linguistics
CMU Advanced NLP Fall 2024 (19): Learning From/For Knowledge Bases
CMU Advanced NLP Fall 2024 (20): Multilingual NLP
CMU Advanced NLP Fall 2024 (21): Safety, Ethics, and Biase in NLP Systems
CMU Advanced NLP Fall 2024 (22): From Decoding to Meta Generation Inference Time Algorithms for LMs
CMU Advanced NLP Fall 2024 (23): MagicPIG & Factor - Methods for Long Context LMs
Graham Neubig
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