16 citations · 37 across the 19 of their papers we have counts for
7 papers · 1 filter
ChatTime: A Unified Multimodal Time Series Foundation Model Bridging Numerical and Textual Data
Chengsen Wang, Qi Qi, Jingyu Wang +5
Human experts typically integrate numerical and textual multimodal information to analyze time series. However, most traditional deep learning predictors rely solely on unimodal nu…
Interdependency Matters: Graph Alignment for Multivariate Time Series Anomaly Detection
Yuanyi Wang, Haifeng Sun, Chengsen Wang +6
Anomaly detection in multivariate time series (MTS) is crucial for various applications in data mining and industry. Current industrial methods typically approach anomaly detection…
Rethinking the Power of Timestamps for Robust Time Series Forecasting: A Global-Local Fusion Perspective
Chengsen Wang, Qi Qi, Jingyu Wang +4
Time series forecasting has played a pivotal role across various industries, including finance, transportation, energy, healthcare, and climate. Due to the abundant seasonal inform…
Multimedia Traffic Anomaly Detection
Tongtong Feng, Qi Qi, Jingyu Wang
Accuracy anomaly detection in user-level social multimedia traffic is crucial for privacy security. Compared with existing models that passively detect specific anomaly classes wit…
OutlierTune: Efficient Channel-Wise Quantization for Large Language Models
Jinguang Wang, Yuexi Yin, Haifeng Sun +5
Quantizing the activations of large language models (LLMs) has been a significant challenge due to the presence of structured outliers. Most existing methods focus on the per-token…
Understanding and Guiding Weakly Supervised Entity Alignment with Potential Isomorphism Propagation
Yuanyi Wang, Wei Tang, Haifeng Sun +5
Weakly Supervised Entity Alignment (EA) is the task of identifying equivalent entities across diverse knowledge graphs (KGs) using only a limited number of seed alignments. Despite…
Gradient Flow of Energy: A General and Efficient Approach for Entity Alignment Decoding
Yuanyi Wang, Haifeng Sun, Jingyu Wang +3
Entity alignment (EA), a pivotal process in integrating multi-source Knowledge Graphs (KGs), seeks to identify equivalent entity pairs across these graphs. Most existing approaches…