RULER (Relative Universal LLM-Elicited Rewards) eliminates the need for hand-crafted reward functions by using an LLM-as-judge to automatically score agent trajectories. Simply define your task in the ...
Abstract: We revisit the problem of predicting the output of an LTI system using offline input-output data in the behavioral setting, without relying on parametric models. Existing works calculate the ...
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