activity
20242026
most citedDMoE: Dual Routing and Dynamic Scheduling for Efficient On-Device MoE-based LLM Serving

7 citations · 9 across the 8 of their papers we have counts for

collaborators

14 papers

cs.RO2026

RedFlow: Redirect Failure into Action-Level Corrections for Flow-matching VLA Policy

Zhengyang Yan, Junhao Li, Fangqi Zhu +6

Flow-matching Vision-Language-Action (VLA) policies have shown strong potential for robotic manipulation but often suffer from compounding errors caused by distribution shifts duri…

cs.LG2026

NASDAQ: Normalized Observation Space Dynamics-Augmented Q-Learning

Xinwei Liu, Junyuan Liang, Zicong Hong +2

Augmenting model-free reinforcement learning (RL) with representations learned through observation dynamics prediction (observation-predictive RL) can improve sample efficiency and…

cs.LG2026

MosaicQuant: Inlier-Outlier Disaggregation for Unified 4-Bit LLM Quantization

Yangjia Hu, Haodong Wang, Zicong Hong +8

4-bit quantization significantly reduces the memory footprint and accelerates the inference of large language models (LLMs). However, its limited bit-width representation struggles…

cs.LG2026

Director: Accelerating Distributed MoE Serving via Online Proactive Expert Placement

Qianli Liu, Kaibin Guo, Zicong Hong +5

Expert parallelism has become the prevailing paradigm to serve Mixture-of-Experts (MoE) models. Its efficiency depends on the communication and computation latencies of the GPUs, w…

cs.RO2026

HALO: A Unified Vision-Language-Action Model for Embodied Multimodal Chain-of-Thought Reasoning

Quanxin Shou, Fangqi Zhu, Shawn Chen +9

Vision-Language-Action (VLA) models have shown strong performance in robotic manipulation, but often struggle in long-horizon or out-of-distribution scenarios due to the lack of ex…

cs.RO2025

WMPO: World Model-based Policy Optimization for Vision-Language-Action Models

Fangqi Zhu, Zhengyang Yan, Zicong Hong +3

Vision-Language-Action (VLA) models have shown strong potential for general-purpose robotic manipulation, but their reliance on expert demonstrations limits their ability to learn…