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Client-specific sufficiency estimation in FedSGA allows for more efficient federated learning, boosting performance while slashing unnecessary computation costs.
A single elastic model can adapt to multiple sparsity configurations without re-optimization, revolutionizing LLM deployment efficiency.
Achieving high-fidelity 3D scene reconstruction from monocular video, ManiSplat enables robots to interact with their environments in a more controllable and realistic manner.
LLMs can now be rigorously benchmarked on realistic sales skills, revealing a wide performance gap where some models rival humans while others fall short.
Streaming 3D reconstruction gets a free lunch: MeMix, a training-free module, slashes reconstruction errors by up to 40% by selectively updating memory patches, fighting catastrophic forgetting without extra parameters.
