5 papers · 1 filter
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…
PostHoc FREE Calibrating on Kolmogorov Arnold Networks
Wenhao Liang, Wei Emma Zhang, Lin Yue +3
Kolmogorov Arnold Networks (KANs) are neural architectures inspired by the Kolmogorov Arnold representation theorem that leverage B Spline parameterizations for flexible, locally a…
Focal Calibration Loss: Controlling Posterior Distortion in Deep Neural Classifiers
Wenhao Liang, Liangwei Zheng, Wei Zhang +1
Confidence calibration matters wherever a classifier's probabilities, not just its labels, are consumed downstream. We study Focal Calibration Loss (FCL), which adds a squared prob…
Correlation Analysis of Adversarial Attack in Time Series Classification
Zhengyang Li, Wenhao Liang, Chang Dong +2
This study investigates the vulnerability of time series classification models to adversarial attacks, with a focus on how these models process local versus global information unde…
Enhancing Financial Market Predictions: Causality-Driven Feature Selection
Wenhao Liang, Zhengyang Li, Weitong Chen
This paper introduces the FinSen dataset that revolutionizes financial market analysis by integrating economic and financial news articles from 197 countries with stock market data…