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Explore the intricacies of reasoning in large language models through this comprehensive conference talk. Delve into various techniques for eliciting and measuring reasoning abilities, including chain of thought prompting, program-aided language models, and plan-and-solve prompting. Discover innovative approaches like self-taught reasoners, specializing smaller models for multi-step reasoning, and iterative prompting methods. Learn about advanced concepts such as tool usage, the REACT framework, and the Chameleon model. Gain valuable insights into the current state and future potential of reasoning capabilities in AI language models, with practical examples and further reading recommendations provided.
