Search papers, labs, and topics across Lattice.
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Achieving 5-7x speedup in diffusion models without sacrificing quality, LinCa redefines the efficiency of feature caching through adaptive prediction strategies.
Privacy-sensitive visual and textual information can be recovered from deep-layer LVLM hidden states, exposing significant risks in collaborative inference.
Achieving competitive performance in Vision-Language Models while reducing computational overhead could revolutionize their deployment on edge devices.
TuringViT outperforms leading ViT models with just 10% of the training data, making state-of-the-art vision technology accessible to a wider audience.
