2 citations · 2 across the 8 of their papers we have counts for
9 papers
FeatFix: Reuse What You Verify through Local Exact-Feature Correction for Faster Cached Diffusion Inference
Hanshuai Cui, Zhiqing Tang, Zhi Yao +3
Diffusion models are widely used to generate high-quality images and videos, but their iterative denoising process remains computationally intensive. A growing class of training-fr…
MemTxn: A Transaction Boundary for Source-Supported Updates and Complete-State Recovery in Agent Memory
Hanshuai Cui, Zhiqing Tang, Zhi Yao +3
Persistent memory lets long-running large language model agents reuse information across sessions and tasks. Yet errors in writable memory can persist and corrupt future behavior.…
LASER: Load-Aware Serving with Early-Exit for Reasoning LLMs at the Edge
Zhiqing Tang, Size Li, Hanshuai Cui +5
Large reasoning models (LRMs) such as DeepSeek-R1 have achieved strong performance through extended chain-of-thought (CoT) generation. However, deploying them on edge devices raise…
RISE: Relay Inference and Online Scheduling for Efficient Edge-Device Collaborative Diffusion Model Services
Zilan Huang, Zhiqing Tang, Hanshuai Cui +4
Text-to-image diffusion models are increasingly deployed at the network edge to serve heterogeneous workloads with diverse quality and latency requirements. However, existing deplo…
CogGuard: Cognitive and Operational Profiling for Proactive Warning in Edge Intelligent Services
Zhi Yao, Weihao Chen, Zhiqing Tang +4
Proactive warning is an important capability for edge intelligent services, where the system predicts whether a subject will successfully complete an incoming task under strict lat…
Semantic Cache Distillation: Efficient State Transfer via Reuse and Selective Patching
Qianli Ma, Zhiqing Tang, Hanshuai Cui +2
Disaggregated serving alleviates memory bottlenecks in Large Language Model (LLM) inference but creates a severe communication bottleneck: transmitting high-dimensional Key-Value (…