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The Hong Kong University of Science and Technology
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Dream-Tac boosts robot manipulation accuracy by over 31% by effectively merging tactile and visual data in real-time.
LLMs can maintain long-context performance even with aggressive KV-cache eviction by learning to predict token importance and compressing evicted tokens into a latent memory.
Key contribution not extracted.
