9 papers
Semantic-Enhanced Time-Series Forecasting via Large Language Models
Hao Liu, Xiaoxing Zhang, Chun Yang +1
Time series forecasting plays a significant role in finance, energy, meteorology, and IoT applications. Recent studies have leveraged the generalization capabilities of large langu…
CHE-TKG: Collaborative Historical Evidence and Evolutionary Dynamics Learning for Temporal Knowledge Graph Reasoning
Shuai-long Lei, Xiaobin Zhu, Jiarui Liang +3
Temporal knowledge graph (TKG) reasoning aims to predict future events from historical facts. A key challenge lies in jointly capturing two sources of predictive information in TKG…
Probabilistic Concept Graph Reasoning for Multimodal Misinformation Detection
Ruichao Yang, Wei Gao, Xiaobin Zhu +5
Multimodal misinformation poses an escalating challenge that often evades traditional detectors, which are opaque black boxes and fragile against new manipulation tactics. We prese…
CID-TKG: Collaborative Historical Invariance and Evolutionary Dynamics Learning for Temporal Knowledge Graph Reasoning
Shuai-Long Lei, Xiaobin Zhu, Jiarui Liang +3
Temporal knowledge graph (TKG) reasoning aims to infer future facts at unseen timestamps from temporally evolving entities and relations. Despite recent progress, existing approach…
DPFlow: Adaptive Optical Flow Estimation with a Dual-Pyramid Framework
Henrique Morimitsu, Xiaobin Zhu, Roberto M. Cesar +2
Optical flow estimation is essential for video processing tasks, such as restoration and action recognition. The quality of videos is constantly increasing, with current standards…
Stationarity Exploration for Multivariate Time Series Forecasting
Hao Liu, Chun Yang, Zhang xiaoxing +2
Deep learning-based time series forecasting has found widespread applications. Recently, converting time series data into the frequency domain for forecasting has become popular fo…