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The Hong Kong University of Science and Technology (Guangzhou)
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SeClaw reveals that existing benchmarks fall short in capturing the complexities of agent behavior, enabling a more nuanced evaluation of security risks in autonomous systems.
Don't let your robot's brief moment of panic get lost in the noise – this new uncertainty method spotlights those critical spikes to predict failures before they happen.
Forget finetuning: this training-free method achieves state-of-the-art zero-shot 3D visual grounding, even in messy, real-world environments.
