1 citations · 1 across the 7 of their papers we have counts for
9 papers
Offline Policy Optimization with Posterior Sampling
Hongqiang Lin, Dongxu Zhang, Yiding Sun +3
A fundamental challenge in model-based offline reinforcement learning (RL) lies in the trade-off between generalization and robustness against exploitation errors in out-of-distrib…
Cooperative Edge Caching with Large Language Model in Wireless Networks
Ning Yang, Wentao Wang, Lingtao Ouyang +1
Cooperative edge caching in overlapping zones couples Base Station (BS) decisions, making content replacement sensitive to spatial topology and temporal reuse. Conventional heurist…
LLM-Driven Large-Scale Spectrum Access
Ning Yang, Jinliang Gao, Haijun Zhang
Efficient spectrum management in massive-scale wireless networks is increasingly challenged by explosive action spaces and the computational intractability of traditional optimizat…
Multi-Turn Reasoning LLMs for Task Offloading in Mobile Edge Computing
Ning Yang, Chuangxin Cheng, Haijun Zhang
Emerging computation-intensive applications impose stringent latency requirements on resource-constrained mobile devices. Mobile Edge Computing (MEC) addresses this challenge throu…
CompilerKV: Risk-Adaptive KV Compression via Offline Experience Compilation
Ning Yang, Chengzhi Wang, Yibo Liu +2
Prefill-only KV compression freezes a token subset at the end of prefill and decodes from it without further eviction. The retention decision is therefore irreversible, yet existin…
Vision-LLMs for Spatiotemporal Traffic Forecasting
Ning Yang, Hengyu Zhong, Haijun Zhang +1
Accurate spatiotemporal traffic forecasting is a critical prerequisite for proactive resource management in dense urban mobile networks. While large language models have shown prom…
Breaking the MoE LLM Trilemma: Dynamic Expert Clustering with Structured Compression
Peijun Zhu, Ning Yang, Baoliang Tian +4
Mixture-of-Experts (MoE) Large Language Models (LLMs) face a trilemma of load imbalance, parameter redundancy, and communication overhead. We introduce a unified framework based on…
Minimizing AoI in Mobile Edge Computing: Nested Index Policy with Preemptive and Non-preemptive Structure
Ning Yang, Yibo Liu, Shuo Chen +2
Mobile Edge Computing (MEC) leverages computational heterogeneity between mobile devices and edge nodes to enable real-time applications requiring high information freshness. The A…
Token-Importance Guided Direct Preference Optimization
Ning Yang, Hai Lin, Yibo Liu +3
Aligning Large Language Models (LLMs) with human preferences is crucial for safe and effective AI interactions. While popular methods like Direct Preference Optimization (DPO) have…