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Explore advanced natural language processing concepts through this comprehensive video lecture series from Carnegie Mellon University's CS 11-711 course taught by Graham Neubig. Master fundamental and cutting-edge NLP techniques starting with word representation and language modeling, then progress through transformer architectures, attention mechanisms, and pre-trained models. Delve into modern approaches including instruction tuning, prompting strategies, complex reasoning, and reinforcement learning from human feedback. Learn practical implementation skills through topics covering retrieval-augmented generation (RAG), model distillation, quantization, and pruning techniques. Examine specialized applications in code and mathematical modeling, long sequence processing, and ensemble methods including mixture of experts. Discover how to build and deploy LLM agents for software development and web browsing, while understanding proper evaluation methodologies and multimodal integration. Gain insights into computational linguistics principles, knowledge base integration, and multilingual NLP systems. Address critical considerations around safety, ethics, and bias in NLP systems, and explore advanced inference-time algorithms including meta-generation and methods for long-context language models through 23 detailed lectures totaling over 27 hours of instruction.
