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Unveiling Typographic Deceptions: Insights of the Typographic Vulnerability in Large Vision-Language Model
Large Vision-Language Models (LVLMs) rely on vision encoders and Large Language Models (LLMs) to exhibit remarkable capabilities on various multi-modal tasks in the joint space of vision and language.
Pursing the Sparse Limitation of Spiking Deep Learning Structures
It posits that within dense neural networks, there exist winning tickets or subnetworks that are sparser but do not compromise performance.
Gaining the Sparse Rewards by Exploring Lottery Tickets in Spiking Neural Network
Deploying energy-efficient deep learning algorithms on computational-limited devices, such as robots, is still a pressing issue for real-world applications.
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