arXiv AI
Aug 25

LLM-based Agents for Forecasting and Prediction: Methods, Training, Evaluation, and Applications

arXiv:2608.23058v1 Announce Type: new Abstract: Large language models (LLMs) now support forecasting systems that combine language-based reasoning with temporal data, evidence retrieval, external too...

By Xiaogang Xu, Jiaqi Tang, Jianmin Chen, Yingying Yan, Zhenchao Tang, Xiangxin Zhou, Xiaobin Hu, Wei Wei, Jinfeng Wu, Qifeng Chen, Lu Zhou, Jiafei Wu, Zhe Liu, Jianwei Yin, Weimin Zheng
arXiv Machine Learning
Jul 28

Foundation Models and Fine-Tuning: Toward a New Generation of Models for Time Series Forecasting

arXiv:2607. 23146v1 Announce Type: new Abstract: Inspired by recent breakthroughs in large language models for natural language processing, foundation models have emerged as a promising paradigm for zero-shot time series forecasting, enabling accurate predictions on datasets never seen during pre-training.

By Morad Laglil, Bertrand Pracca, Emilie Devijver, Eric Gaussier