4 papers
MoRA: MoE Pruning via Router Bias Learning and Expert Approximation
Yushuai Sun, Zikun Zhou, Lin Gao +2
Mixture-of-Experts (MoE) models enable parameter scaling with limited per-token computation by activating only a small subset of experts for each token, but deploying them still re…
Representation Dynamics Reveal Semantic Saliency and Similarity for Visual Token Pruning in MLLMs
Weixuan Li, Zikun Zhou, Xinyi Zhuang +4
Multimodal large language models (MLLMs) incur high inference latency from long visual token sequences. Existing pruning methods commonly use attention maps or output features to e…
Joint Communication and Computation Scheduling for MEC-enabled AIGC Services: A Game-Theoretic Stochastic Learning Approach
Huaizhe Liu, Xinyi Zhuang, Jiaqi Wu +3
Artificial Intelligence Generated Content (AIGC) powered by Generative Diffusion Models (GDMs) has emerged as a transformative paradigm for automated content creation. To satisfy t…
Joint Edge Server Deployment and Computation Offloading: A Multi-Timescale Stochastic Programming Framework
Huaizhe Liu, Jiaqi Wu, Zhizongkai Wang +2
Mobile Edge Computing (MEC) is a promising approach for enhancing the quality-of-service (QoS) of AI-enabled applications in the B5G/6G era, by bringing computation capability clos…