Researchers from Stanford, NVIDIA, and UT Austin Propose Cross-Episodic Curriculum (CEC): A New Artificial Intelligence Algorithm to Boost the Learning Efficiency and Generalization of Transformer Agents

Sequential decision-making problems are undergoing a major transition due to the paradigm shift brought about by the introduction of foundation models. These models, such as transformer models, have completely changed a number of fields, including planning, control, and pre-trained visual representation. Despite these impressive developments, applying these data-hungry algorithms to fields like robotics with less […]

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