works on

From the 1 of 8 linked papers with an AI index.

activity
20242026
collaborators

8 papers

cs.CR2026

MemPoison: Uncovering Persistent Memory Threats and Structural Blind Spots in LLM Agents

Jifeng Gao, Kang Xia, Yi Zhang +5

The paper introduces MemPoison, a benchmark and analysis framework that studies how adversarial content can be injected into the persistent external memory of large language model…

cs.CV2026

Multimodal Graph Representation Learning with Dynamic Information Pathways

Xiaobin Hong, Mingkai Lin, Xiaoli Wang +2

Multimodal graphs, where nodes contain heterogeneous features such as images and text, are increasingly common in real-world applications. Effectively learning on such graphs requi…

cs.AI2025

Energy-Aware Pattern Disentanglement: A Generalizable Pattern Assisted Architecture for Multi-task Time Series Analysis

Xiangkai Ma, Xiaobin Hong, Wenzhong Li +1

Time series analysis has found widespread applications in areas such as weather forecasting, anomaly detection, and healthcare. While deep learning approaches have achieved signifi…

cs.LG2025

Domain Fusion Controllable Generalization for Cross-Domain Time Series Forecasting from Multi-Domain Integrated Distribution

Xiangkai Ma, Xiaobin Hong, Mingkai Lin +3

Conventional deep models have achieved unprecedented success in time series forecasting. However, facing the challenge of cross-domain generalization, existing studies utilize stat…

cs.CV2025

Semantic-Supervised Spatial-Temporal Fusion for LiDAR-based 3D Object Detection

Chaoqun Wang, Xiaobin Hong, Wenzhong Li +1

LiDAR-based 3D object detection presents significant challenges due to the inherent sparsity of LiDAR points. A common solution involves long-term temporal LiDAR data to densify th…

cs.LG2025

Unify and Anchor: A Context-Aware Transformer for Cross-Domain Time Series Forecasting

Xiaobin Hong, Jiawen Zhang, Wenzhong Li +2

The rise of foundation models has revolutionized natural language processing and computer vision, yet their best practices to time series forecasting remains underexplored. Existin…