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Plan evaluators can reward a strategic plan for becoming less explicit. This paper studies that failure in a staged e...
Simulation-based algorithms are especially suited for high-uncertainty environments such as adversarial board games w...
Automatic speech recognition is dominated by autoregressive decoders that emit one token at a time. We ask whether a ...
Large Language Model (LLM) agents have moved beyond generating responses to executing multi-step tasks by calling too...
Training robust autonomous driving agents requires a simulator that is fast enough for reinforcement learning at scal...
Large language model (LLM) agents increasingly automate multi-step engineering and informatics workflows, yet they ra...
LLM-based coding agents have significantly advanced automated software issue resolution, yet they remain highly prone...
In this paper, we propose SpectraReward, a training-free reward function that turns pretrained MLLMs into off-the-she...
Generating and editing a person's face demands high precision, as even minor modifications can significantly alter a ...
Steerability is a defining capability of generalist robot policies, yet remains largely absent in dexterous-hand syst...
Recent foundation image and video generation models offer strong generalization and controllability, but their direct...
Why does contrastive learning with simple images and augmentations yield useful representations for downstream tasks?...