LSTPrompt: Large Language Models as Zero-Shot Time Series Forecasters by Long-Short-Term Prompting

no code implementations • 25 Feb 2024 • Haoxin Liu, Zhiyuan Zhao, Jindong Wang, Harshavardhan Kamarthi, B. Aditya Prakash

Time-series forecasting (TSF) finds broad applications in real-world scenarios.

Computational Efficiency Time Series +1

Few-Shot Learning for Chronic Disease Management: Leveraging Large Language Models and Multi-Prompt Engineering with Medical Knowledge Injection

no code implementations • 16 Jan 2024 • Haoxin Liu, Wenli Zhang, Jiaheng Xie, Buomsoo Kim, Zhu Zhang, Yidong Chai

On the depression detection task, our method (F1 = 0. 975~0. 978) significantly outperforms traditional supervised learning paradigms, including feature engineering (F1 = 0. 760) and architecture engineering (F1 = 0. 756).

Depression Detection Feature Engineering +3

Towards Unsupervised Domain Generalization

no code implementations • CVPR 2022 • Xingxuan Zhang, Linjun Zhou, Renzhe Xu, Peng Cui, Zheyan Shen, Haoxin Liu

Domain generalization (DG) aims to help models trained on a set of source domains generalize better on unseen target domains.

Domain Generalization Representation Learning