3 papers
eess.SP2026
TimeRFT: Stimulating Generalizable Time Series Forecasting for TSFMs via Reinforcement Finetuning
Siyang Li, Yize Chen, Zijie Zhu +4
Time Series Foundation Models (TSFMs) have demonstrated strong generalization capability and data efficiency in time series forecasting through large-scale pretraining. However, ad…
cs.LG2026
Towards Generalizable PDE Dynamics Forecasting via Physics-Guided Invariant Learning
Siyang Li, Yize Chen, Yan Guo +2
Advanced deep learning-based approaches have been actively applied to forecast the spatiotemporal physical dynamics governed by partial differential equations (PDEs), which acts as…
cs.LG2026
STO-RL: Offline RL under Sparse Rewards via LLM-Guided Subgoal Temporal Order
Chengyang Gu, Yuxin Pan, Hui Xiong +1
Offline reinforcement learning (RL) enables policy learning from pre-collected datasets, avoiding costly and risky online interactions, but it often struggles with long-horizon tas…