Dayang Li

Domain-knowledge-guided deep learning for probabilistic precipitation downscaling over southeastern Tibetan Plateau

Dayang Li, Baoxiang Pan, Yuan Liu, Ashish Sharma et autres

cn, us, au (code pays fourni par la source)

Added Values of Convection-Permitting Models for Extreme Precipitation over the Southeastern Tibetan Plateau

Dayang Li, Yi Yao, Yan Zhou

The southeastern Tibetan Plateau (SETP) lies at the intersection of extreme topography and the Indian summer monsoon, producing intense orographically driven precipitation. Resolving these extremes requires convection-permitting simulations (CPMs) due to the combined influence of complex terrain and vigorous convection. However, kilometer-scale …

cn (code pays fourni par la source)

Efficient precipitation downscaling over the Southern Tibetan Plateau with deep learning surrogates

Dayang Li, Yi Yang, Yan Zhou, Fuqiang Tian et autres

cn, hk (code pays fourni par la source)

Correct When Paired, Wrong When Split: Decoupling and Editing Modality-Specific Neurons in MLLMs

Tingchao Fu, Wenkai Wang, Fanxiao Li, Huadong Zhang et autres

Although Knowledge Editing provides an efficient mechanism for updating the knowledge of Multimodal Large Language Models (MLLMs), we find that current paradigms still suffer from an important yet remain underexplored issue : editing decoupling failure, where entity-related knowledge can be updated when …

Field-Scale Detection of Rice Bacterial Leaf Blight Using UAV-Based Multispectral Imagery: Via Cross-Scale Sample-Label Transfer and Spatial–Spectral Feature Fusion

Huiqin Ma, Zhiqin Gui, Yujin Jing, Dongmei Chen et autres

Accurate field-scale crop disease detection is crucial for precise decisions and for highly efficient multi-scale collaboration. UAV-based multispectral imaging technology offers advantages in terms of high efficiency and low cost. Deep learning shows potential for deep representation and fusion of spectral and …

cn (code pays fourni par la source)

Correct When Paired, Wrong When Split: Decoupling and Editing Modality-Specific Neurons in MLLMs

Tingchao Fu, Wenkai Wang, Fanxiao Li, Huadong Zhang et autres

Tingchao Fu, Wenkai Wang, Fanxiao Li, Huadong Zhang, Jinhong Zhang, Dayang Li, Yunyun Dong, Renyang Liu, Wei Zhou. Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). 2026.

cn, sg (code pays fourni par la source)

Spatially coherent changes in Chinese annual flood peaks revealed by a consensus-based machine learning framework for regionalization

Jiaze Weng, Yixin Yang, Dayang Li, Ashish Sharma et autres

cn, au (code pays fourni par la source)

FPGA-based Mb2DKDNet for field disease and pest diagnosis

Dongmei Chen, Dayang Li, Jingwen Zheng, Yulin Cai et autres

• Proposed Mb2DKDNet model for intelligent diagnosis of rice pests and diseases in the field. • Constructed MIRD dataset covering diverse regions and rice growth stages. • Deployed on FPGA to enable efficient real-time diagnosis in agricultural machinery. • Achieved 98.07 % …

cn (code pays fourni par la source)

Agricultural policy finance and rural employment: a perspective on county-level educational resource allocation

Dayang Li, Jiahui Ling

Examining the impact of agricultural policy finance on rural employment, as well as the underlying mechanisms, is of paramount importance for advancing rural financial development and achieving the goal of common prosperity in China. Drawing on county-level panel data from 2007 to …

cn, kr (code pays fourni par la source)

High-efficiency real-time rice leaf disease classification using convolutional neural network accelerator on FPGA for edge computing in precision agriculture

Jingwen Zheng, Zhengbing Lv, Dayang Li, Chengbo Lu et autres

cn (code pays fourni par la source)

FPGA-Based Low-Power High-Performance CNN Accelerator Integrating DIST for Rice Leaf Disease Classification

Jingwen Zheng, Zhengbing Lv, Dayang Li, Chengbo Lu et autres

Agricultural pest and disease monitoring has recently become a crucial aspect of modern agriculture. Toward this end, this study investigates methodologies for implementing low-power, high-performance convolutional neural networks (CNNs) on agricultural edge detection devices. Recognizing the potential of field-programmable gate arrays (FPGAs) …

cn (code pays fourni par la source)

Prior knowledge-constrained deep learning for probabilistic precipitation downscaling

Dayang Li, Long Yang, Baoxiang Pan, Yuan Liu

Precipitation downscaling, particularly at convection-permitting scales (less than 4 km), is highly uncertain. This is especially pronounced in mountainous regions due to the interplay of complex topography and atmospheric dynamics. It impedes reliable estimation of variability and risks in localized extreme rainstorms. …

cn, us (code pays fourni par la source)