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Found 2 papers, 1 papers with code
Vision-Language Models as a Source of Rewards
Building generalist agents that can accomplish many goals in rich open-ended environments is one of the research frontiers for reinforcement learning.
Uncertainty Quantification for Local Model Explanations Without Model Access
We present a model-agnostic algorithm for generating post-hoc explanations and uncertainty intervals for a machine learning model when only a static sample of inputs and outputs from the model is available, rather than direct access to the model itself.
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