Ruichen Zhang
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The paper proposes eSpat-B and eSpat+ systems to enable efficient and privacy-preserving distribution statistics analysis on massive, dynamic mobile spatial data.
This paper proposes SkyChain Intelligence, a framework that integrates agentic AI, consortium blockchain, and Multi-Agent Deep Reinforcement Learning to optimize autonomy, security, and efficiency in Low-Altitude Economy ecosystems.
This paper proposes Learning to Allocate (L2A), an end-to-end framework for resource-adaptive inference in Large Language Models (LLMs) using budget-conditioned and input-aware gating networks.
Papers
End-to-End Dynamic Sparsity for Resource-Adaptive LLM Inference
Yuhang Chen, Jinhao Duan, Ruichen Zhang, Mingfu Liang +10 more
This paper proposes Learning to Allocate (L2A), an end-to-end framework for resource-adaptive inference in Large Language Models (LLMs) using budget-conditioned and input-aware gating networks.