15 papers
Self-Gating Attention for Efficient Time Series Forecasting
Dezheng Wang, Tong Chen, Wei Yuan +3
Transformer architectures have shown strong potential in time series forecasting, where multi-head self-attention is widely used to capture temporal dependencies across historical…
LEFT: Learnable Fusion of Tri-view Tokens for Unsupervised Time Series Anomaly Detection
Dezheng Wang, Tong Chen, Guansong Pang +3
As a fundamental data mining task, unsupervised time series anomaly detection (TSAD) aims to build a model for identifying abnormal timestamps without assuming the availability of…
FOSTER: First-order Dataset Distillation for Text-based Sequential Recommendation
Hung Vinh Tran, Tong Chen, Xinyi Gao +3
Text-based sequential recommender systems, while greatly improving recommendation accuracy by incorporating item contexts, are undeniably more expensive to train. By condensing a l…
GRAFT: Graph-Tokenized LLMs for Tool Planning
Xinyi Gao, Xinyu Ren, Junliang Yu +3
Large language models (LLMs) are increasingly used to complete complex tasks by selecting and coordinating external tools across multiple steps. This requires aligning tool choices…
Prompt-Unknown Promotion Attacks against LLM-based Sequential Recommender Systems
Yuchuan Zhao, Tong Chen, Junliang Yu +3
Large language model-powered sequential recommender systems (LLM-SRSs) have recently demonstrated remarkable performance, enabling recommendations through prompt-driven inference o…
Evolutionary Router Feature Generation for Zero-Shot Graph Anomaly Detection with Mixture-of-Experts
Haiyang Jiang, Tong Chen, Xinyi Gao +3
Zero-shot graph anomaly detection (GAD) has attracted increasing attention recent years, yet the heterogeneity of graph structures, features, and anomaly patterns across graphs mak…