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Achieving a 0.499 face similarity score, WithEveryone revolutionizes group image generation by ensuring identity preservation for up to ten individuals without direct face copying.
VA-Judger transforms reward modeling by integrating human preference feedback, leading to coherent and high-quality video-audio generation that outperforms traditional metrics.
J64 reveals hidden reasoning states that can significantly boost model accuracy and decision-making, while R64 provides a lightweight, effective proxy for deployment.
Bridging the gap between human and robotic manipulation, HandEdit enables scalable learning for dexterous robotics using abundant egocentric video data.
Robots can now learn from their experiences and adapt in real-time, paving the way for a new era of general-purpose robotic agents.
Environment evolution can reveal 17% more safety failures in complex tasks compared to static benchmarks, reshaping our understanding of agent vulnerabilities.
Frontier LLMs may appear safe, but they produce harmful content at scale, with risks growing as model capabilities increase.
