10 papers
Large Language Model-Assisted Systematic Study of Anomalous Adsorption Phenomena
Fengxu Yang, Matthew L. Schneider, Weitong Chen +1
Soft porous crystals can undergo guest-induced structural transitions producing unconventional adsorption isotherms, which are valuable for gas separation and storage applications.…
Large language models in materials science and the need for open-source approaches
Fengxu Yang, Weitong Chen, Jack D. Evans
Large language models (LLMs) are rapidly transforming materials science. This review examines recent LLM applications across the materials discovery pipeline, focusing on three key…
TrojanTime: Backdoor Attacks on Time Series Classification
Chang Dong, Zechao Sun, Guangdong Bai +3
Time Series Classification (TSC) is highly vulnerable to backdoor attacks, posing significant security threats. Existing methods primarily focus on data poisoning during the traini…
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…
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…
AWF: Adaptive Weight Fusion for Enhanced Class Incremental Semantic Segmentation
Zechao Sun, Shuying Piao, Haolin Jin +4
Class Incremental Semantic Segmentation (CISS) aims to mitigate catastrophic forgetting by maintaining a balance between previously learned and newly introduced knowledge. Existing…
Improving Time Series Classification with Representation Soft Label Smoothing
Hengyi Ma, Weitong Chen
Previous research has indicated that deep neural network based models for time series classification (TSC) tasks are prone to overfitting. This issue can be mitigated by employing…
Evaluating Model Robustness Using Adaptive Sparse L0 Regularization
Weiyou Liu, Zhenyang Li, Weitong Chen
Deep Neural Networks have demonstrated remarkable success in various domains but remain susceptible to adversarial examples, which are slightly altered inputs designed to induce mi…
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…