4 papers
Semantics-Enhanced Retrieval-Augmented Time Series Forecasting
Shiqiao Zhou, Zipeng Wu, Holger Schöner +3
Time series forecasting models often benefit from historical patterns. Inspired by Retrieval-Augmented Generation (RAG), recent research explored retrieving relevant historical tim…
Stationarity-Aware Retrieval-Augmented Time Series Forecasting
Shiqiao Zhou, Holger Schöner, Zipeng Wu +3
Time series forecasting relies on historical patterns, but real-world series often exhibit non-stationarity and regime shifts that challenge fully parametric forecasters. Inspired…
Uncertainty-Aware Offline Data-Driven Multi-Objective Optimization
Huanbo Lyu, Miqing Li, Shiqiao Zhou +7
In offline data-driven multi-objective optimization (MOO), optimization is performed using surrogate models trained only on an offline dataset. These surrogate models contain inher…
BALM-TSF: Balanced Multimodal Alignment for LLM-Based Time Series Forecasting
Shiqiao Zhou, Holger Schöner, Huanbo Lyu +2
Time series forecasting is a long-standing and highly challenging research topic. Recently, driven by the rise of large language models (LLMs), research has increasingly shifted fr…