Yongji Wu — accepted AI-conference papers

2026

ConServe: Fine-Grained GPU Harvesting for LLM Online and Offline Co-Serving

Yifan Qiao, Shan Yu, Shu Anzai, Haoran Ma, Shuo Yang, Yang Wang +7

ICML 2026poster

Large language model (LLM) serving demands low latency and high throughput, but high load variability leads to significant GPU utilization. In this paper, we identify a synergetic but overlooked opportunity to co-serve latency-critical online requests alongside *latency-tolerant offline* tasks, whic…

Cited by 0 Source ↗Scholar ↗

2026

RLux-VLA: A Unified and Efficient Framework for Reinforcement Learning of Vision-Language-Action Models

Hongzhi Zang, Mingjie Wei, Si Xu, Yongji Wu, Zhen Guo, Yuanqing Wang +14

RSS 2026poster

Recent advances in vision-language-action (VLA) models have motivated the extension of their capabilities to embodied settings, where reinforcement learning (RL) offers a principled way to optimize task success through interaction. However, existing methods remain fragmented, lacking both a unified …

Cited by 0 Source ↗Scholar ↗