Shuo Wang

Assisting Mission-Critical Traffic Flows with Active Queue Management in Industrial Internet of Things

Shuo Wang, Jonathan Kua, Jiong Jin, Yew Wee Wong, Prem Prakash Jayaraman, Zhibo Pang

Mission-critical Industrial Internet of Things (IIoT) traffic flows require bounded network latency and jitter guarantees to ensure the safe functioning of critical industrial infrastructure. These flows are typically communicated via commodity network routers with conventional F…Read more

Robustifying Vision-Language Models via Test-Time Prompt Adaptation

Xingyu Zhu, Huanshen Wu, Shuo Wang, Beier Zhu, Jiannan Ge, Jiaheng Zhang, et al.

Pre-trained Vision-Language Models (VLMs) such as CLIP achieve strong zero-shot generalization, but their performance degrades sharply under adversarial perturbations. Existing test-time adaptation methods typically rely on sample-level confidence heuristics, overlooking the intr…Read more

Dive Into the Implicit Biases of Low-rank Vision-language Alignment

Mingjia Shi, Shuo Wang, Xiaobo Wang, Sifan Zhou, Kai Wang, Tianyu Fu, et al.

Vision-language alignment, the stage that bridges pretrained vision encoders and large language models, is widely treated as a form of pretraining requiring full-parameter updates. We challenge this view and investigate what happens when low-rank adaptation is applied to the LLM…Read more

WebRetriever: A Large-Scale Comprehensive Benchmark for Efficient Web Agent Evaluation

Wei Dong, Tianyu Fu, Zhe Yu, Hanning Wang, Anyang Su, Zhizhou Fang, et al.

As web agents increasingly demonstrate capabilities in automated task execution, the development of robust evaluation frameworks for assessing their navigation and task completion performance has emerged as a critical research priority. However, existing benchmarks exhibit fundam…Read more

CAT: Confidence-Adaptive Thinking for Efficient Reasoning of Large Reasoning Models

Qizhi Jiang, Shuo Wang, Pei Ke, Yuhang Song, Ke Qin

Large Reasoning Models (LRMs) have achieved remarkable success on complex tasks by leveraging long chain-of-thought (CoT) trajectories, yet they frequently exhibit overthinking on simple queries, resulting in significant token overhead and reduced inference efficiency. However, e…Read more

From Pixels to Temporal Correlations: Learning Informative Representations for Reinforcement Learning Pre-training

Jinwen Wang, Youfang Lin, Xiaobo Hu, Siyu Yang, Sheng Han, Shuo Wang, et al.

Unsupervised pre-training on large-scale datasets has demonstrated significant potential for improving the sample efficiency and performance of Reinforcement Learning (RL). Given the large-scale action-free internet videos, existing methods utilize single-step transition predicti…Read more

Local Motion Matters: A Deconstruct-Recompose Paradigm for Reinforcement Learning Pre-training from Videos

Jinwen Wang, Youfang Lin, Xiaobo Hu, Shuo Wang, Kai Lv

Pre-training on large-scale videos to improve reinforcement learning efficiency is promising yet remains challenging. Existing methods typically treat the agent as an indivisible entity, modeling motion patterns globally. Such global modeling is tightly coupled with the morpholog…Read more

Task-Relevant Representation Decoupling for Visual Reinforcement Learning Generalization

Jinwen Wang, Youfang Lin, Xiaobo Hu, Qian Xu, Shuo Wang, Zhuo Chen, et al.

Visual Reinforcement Learning (VRL) has achieved considerable success in solving control tasks. However, generalizing learned policies to new environments remains a major challenge, as agents often overfit to task-irrelevant features in the training environment. To solve this pro…Read more

Labimus: A Simulation and Benchmark for Humanoid Dexterous Manipulation in Chemical Laboratory

Yuhan Wu, Zhao Jin, Tao Li, Yuheng Zhang, Zhichao Wang, Shuo Wang, et al.

Laboratory automation has made remarkable progress through robotic platforms and AI-driven scientific reasoning. However, many laboratory operations (e.g., solid--solid transfer) remain inherently dynamic and require real-time adaptation to different materials and experimental co…Read more

Rank-In Integrated Machine Learning and Bioinformatic Analysis Identified the Key Genes in HFPO-DA (GenX) Exposure to Human, Mouse, and Rat Organisms

Xinyang Li, Hua Xiao, Liye Zhu, Qisijing Liu, Bowei Zhang, Jin Wang, et al.

Hexafluoropropylene Oxide Dimer Acid (HFPO-DA or GenX) is a pervasive perfluorinated compound with scant understood toxic effects. Toxicological studies on GenX have been conducted using animal models. To research deeper into the potential toxicity of GenX in humans and animals,…Read more

Dimension-aware six degrees of freedom pose estimation for robotic rebar tying in prefabricated construction

Mi Liu, Jingjing Guo, Lu Deng, Shuo Wang, S. Zou, Peng Shi, et al.