Multimodal applications such as educational assistants and medical diagnosis demand high concurrency and low latency, and are increasingly served by edge inference enhanced with Retrieval-Augmented Generation (RAG). However, heterogeneous multimodal models and fragmented edge resources couple three problems that prior...
Zhi Yao, Zhi-Qing Tang, Han-Shuai Cui et al.· IEEE Transactions on Paralle...· 0 citations
FeatFix is introduced, a local exact-feature correction method for cached diffusion inference that replaces the complete draft block output with the exact output computed from the same incoming state, avoiding token- or channel-level partial replacement and full-timestep recomputation.
Han-Shuai Cui, Zhiqing Tang, Z. Yao et al.· arXiv.org· 0 citations
MemTxn is a governance layer outside the answer model that verifies whether an update is supported by its source and restores the application-visible state after a fault, and achieves the highest average F1 across all twelve answer-model configurations.
Han-Shuai Cui, Zhiqing Tang, Z. Yao et al.· arXiv.org· 2 citations
This work introduces a diffusion model as a generative prior to produce high-quality global deployment plans, effectively avoiding the local-optima problem common in conventional reinforcement learning.
Jie Gao, Xing-Dan Wang, Zhi-Qing Tang et al.· Tsinghua Science and Technol...· 0 citations
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.
