Tag: UC Berkeley

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Yann LeCun Team Uses Dictionary Learning To Peek Into Transformers’ Black Boxes

A Yann LeCun team proposes dictionary learning to provide detailed visualizations of transformer representations and insights into semantic structures such as word-level disambiguation, sentence-level pattern formation, and long-range dependency captured by transformers.

AI Research

Get a Grip! Berkeley Targets Dexterous Manipulation Using Deep RL

UC Berkeley researchers have published a paper demonstrating how Deep Reinforcement Learning can be used to control dexterous robot hands for complicated tasks. Learning Complex Dexterous Manipulation with Deep Reinforcement Learning and Demonstrations proposes a low-cost and high-efficiency control method that uses demonstration and simulation techniques to accelerate the learning process.