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Beijing University of Posts and Telecommunications, Tsinghua University, Shanghai Jiao Tong University
Tsinghua AI4
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Current memory agents fail to provide reliable governance in shared settings, with no method achieving a balance between utility, access control, and forgetting.
Effective personalization in presentation generation hinges on a novel memory architecture that distinguishes between user profiles, session constraints, and execution history.
Image-conditioned video diffusion models can now be fine-tuned to produce more realistic motion dynamics and long-term temporal coherence via a novel reward-driven approach that avoids common pitfalls like reward hacking.
Forget retraining: OmniVTON++ achieves state-of-the-art virtual try-on across diverse datasets and garment types using a completely training-free approach.
