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Harbin Institute of Technology, Great Bay University, Robotics
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Treating tactile signals as active cues rather than passive inputs leads to a dramatic boost in manipulation success rates and accuracy in contact-rich tasks.
Forged watermarks in latent diffusion models are fundamentally limited by an irreducible distortion floor, revealing critical vulnerabilities in black-box settings.
Orca's unified world latent space enables superior performance in diverse tasks, outperforming specialized models with a single framework.
Current vision-language models falter in streaming interaction understanding, with alarming mis-calibration leading to confidently incorrect predictions.
Complex visual queries can significantly elevate the reasoning capabilities of multi-modal large language models, revealing new dimensions in AI's understanding of abstract visual content.
