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This lecture covers the concept of decoding from neural models in modern NLP, focusing on encoder-decoder models and the decoding algorithm. It explains the main idea of decoding, issues with argmax decoding, and introduces beam search as an alternative. The instructor also discusses the effect of beam size and what to expect in the upcoming lectures.