3 papers
cs.LG2026
REATS: LLM Reasoning-based Ensemble Learning for Adaptive Time Series Forecasting
Xu Zhang, Chang Xu, Hui Sun +5
Due to the diversity of real-world time series, no single forecasting model consistently dominates across all samples. Ensemble learning addresses this by combining complementary m…
cs.LG2026
SEMixer: Semantics Enhanced MLP-Mixer for Multiscale Mixing and Long-term Time Series Forecasting
Xu Zhang, Qitong Wang, Peng Wang +1
Modeling multiscale patterns is crucial for long-term time series forecasting (TSF). However, redundancy and noise in time series, together with semantic gaps between non-adjacent…
cs.LG2026
Amortized Predictability-aware Training Framework for Time Series Forecasting and Classification
Xu Zhang, Peng Wang, Yichen Li +1
Time series data are prone to noise in various domains, and training samples may contain low-predictability patterns that deviate from the normal data distribution, leading to trai…