Wei Zhou

Estimation of leaf nitrogen concentration at different leaf positions in rice based on UAV RGB images combined with machine-learning algorithms

Boteng Sun, Wei Zhou, Songde Huang, Qi Liu, Shilin Zhu, Jinyue Guo, et al.

Climate-resilient electric vehicle charging infrastructure for sustainable cities: An interpretable causal-ensemble framework for preventive maintenance and low-carbon mobility

Cande Lian, Wentao Zeng, Jiabin Wu, Yiming Bie, Wei Zhou

Reliable electric vehicle (EV) charging infrastructure is a cornerstone of sustainable, low-carbon cities, yet urban climate stress such as extreme heat, heavy precipitation, and humidity increasingly raises equipment fault risk and undermines the resilience of urban energy and m…Read more

CRISP: Pre-LLM Yet Text-Driven Visual Token Pruning for Efficient LVLM Inference

Xu Li, Yi Zheng, Mengyang Zhao, Yuxuan Liang, Zhe Liu, Rui Zhu, et al.

Large Vision-Language Models (LVLMs) typically require processing hundreds to thousands of visual tokens, leading to substantial inference overhead. Existing visual token pruning methods either operate before the LLM using text-agnostic heuristics or prune inside the LLM at the c…Read more

PFAdapter: Hierarchical LoRA Decomposition for Personalized Federated MLLMs

Jing Liu, Kun Yang, Yan Wang, Dingkang Yang, Xiaoshuai Hao, Wei Zhang, et al.

Agentic AI systems are reshaping communications and networking by deploying autonomous intelligent agents capable of collaborative learning while maintaining data privacy at network edges. Within distributed network environments, Multimodal Large Language Models (MLLMs) serve as…Read more

Large Language Models in Misinformation Ecosystems: Misuse, Defense, and Vulnerability

Lingwei Wei, Dou Hu, Wei Zhou, Songlin Hu, Philip S. Yu

Large language models (LLMs) have transformed misinformation from a primarily content-centric problem into a broader ecosystem-level security challenge. When misused, LLMs create risks beyond false content generation, enabling attacks on the social contexts, evidence sources, ret…Read more

PS4: Proxy-Supervised Joint Training for Real Target Speaker Extraction

Wanyi Ning, Wei Zhou, Yingpeng Li, Yinshang Guo, Haitao Qian, Yiming Cheng

Training target speaker extraction (TSE) models for real conversational mixtures remains challenging because large-scale training corpora and clean target speech for supervision are unavailable. We present PS4, a proxy-supervised training framework for TSE in real conversational…Read more

STAPO: Selective Trajectory-Aware Policy Optimization for LLM Agent Training

Qiuyi Qi, Tian Liang, Mutian Bao, Jinjian Zhang, Dongnan Liu, Wei Zhou, et al.

Reinforcement Learning (RL) is the dominant paradigm for training Large Language Model (LLM) agents on long-horizon tasks. However, sparse and delayed rewards often lead to trajectory neglect, in which agents lose focus on the task goal and interaction history at intermediate ste…Read more

CARL: Constraint-Aware Reinforcement Learning for Planning with LLMs

Qiuyi Qi, Jinjian Zhang, Mutian Bao, Tian Liang, Guocong Li, Dongnan Liu, et al.

Despite their strong reasoning capabilities and extensive world knowledge, Large Language Models (LLMs) frequently generate plans that violate task constraints, undermining their reliability in real-world applications. This deficiency arises from a lack of systematic mechanisms t…Read more

WBMM: Windowed Batch Matrix Multiplication for Efficient Large Receptive Field Convolution

Wan Song, Wei Zhou, Rui Wang, Jun Yu, Toru Kurihara, Jiajia Xu, et al.

Large kernel depthwise convolutions achieve strong performance but suffer from significant degradation as kernel size grows due to irregular memory access from gather-based computation; while Large Kernel Acceleration (LKA) helps on small feature maps, it becomes counterproductiv…Read more

The Turning Point of 3D Plant Phenotyping: 3D Foundation Models Enable Minute-to-Second Cross-Crop Reconstruction and Beyond

Hanyue Jia, Wei Zhou, Wenbo Zhou, Yanan Li, Hao Lu, Tingting Wu

3D plant phenotyping is notoriously known to be procedure-complicated and of low throughput due to the extensive multi-view imaging, the fragile 3D reconstruction pipeline, and the additional cost from reconstructed geometry to phenotypic extraction. These limitations are further…Read more

Additive Causal Construction for Transferable and Reconfigurable Cross-System Learning in Multi-Source Image Fusion

Zhizhong Fu, Wei Zhou, Zhaoyang Jiang, Yulong Lin, Yifu Hou, Xiaorong Ding, et al.

In multi-source image fusion scenarios, heterogeneous inputs are typically driven by distinct generative mechanisms and can be viewed as a composition of multiple causal systems. However, cross-system discrepancy (CSD) and cross-system entanglement (CSE) commonly arise during the…Read more

DanceOPD: On-Policy Generative Field Distillation

Wei Zhou, Xiongwei Zhu, Zelin Xu, Bo Dong, Lixue Gong, Yongyuan Liang, et al.

Modern image generation demands a single model that unifies diverse capabilities, including text-to-image (T2I), local editing, and global editing. However, these capabilities are rarely naturally aligned and often conflict. For instance, editing tends to degrade T2I performance,…Read more

Early Driver Fatigue Detection System: A Cost-Effective and Wearable Approach Utilizing Embedded Machine Learning

Chengyou Lin, Xinying Zhu, Renpeng Wang, Wei Zhou, Na Li, Yu Xie

Driving fatigue is the cause of many traffic accidents and poses a serious threat to road safety. To address this issue, this paper aims to develop a system for the early detection of driver fatigue. The system leverages heart rate variability (HRV) features and embedded machine…Read more