5 citations · 7 across the 5 of their papers we have counts for
6 papers
Lifting Manifolds to Mitigate Pseudo-Alignment in LLM4TS
Liangwei Nathan Zheng, Wenhao Liang, Wei Emma Zhang +3
Pseudo-Alignment is a pervasive challenge in many large language models for time series (LLM4TS) models, often causing them to underperform compared to linear models or randomly in…
Irregularity-Informed Time Series Analysis: Adaptive Modelling of Spatial and Temporal Dynamics
Liangwei Nathan Zheng, Zhengyang Li, Chang George Dong +5
Irregular Time Series Data (IRTS) has shown increasing prevalence in real-world applications. We observed that IRTS can be divided into two specialized types: Natural Irregular Tim…
Devil in the Tail: A Multi-Modal Framework for Drug-Drug Interaction Prediction in Long Tail Distinction
Liangwei Nathan Zheng, Chang George Dong, Wei Emma Zhang +3
Drug-drug interaction (DDI) identification is a crucial aspect of pharmacology research. There are many DDI types (hundreds), and they are not evenly distributed with equal chance…
Understanding Why Large Language Models Can Be Ineffective in Time Series Analysis: The Impact of Modality Alignment
Liangwei Nathan Zheng, Chang George Dong, Wei Emma Zhang +4
Large Language Models (LLMs) have demonstrated impressive performance in time series analysis and seems to understand the time temporal relationship well than traditional transform…
Boosting Certified Robustness for Time Series Classification with Efficient Self-Ensemble
Chang Dong, Zhengyang Li, Liangwei Zheng +2
Recently, the issue of adversarial robustness in the time series domain has garnered significant attention. However, the available defense mechanisms remain limited, with adversari…
Kolmogorov-Arnold Networks (KAN) for Time Series Classification and Robust Analysis
Chang Dong, Liangwei Zheng, Weitong Chen
Kolmogorov-Arnold Networks (KAN) has recently attracted significant attention as a promising alternative to traditional Multi-Layer Perceptrons (MLP). Despite their theoretical app…