3 papers
cs.MA2026
MAGIC: Multi-Step Advantage-Gated Causal Influence for Multi-agent Reinforcement Learning
Haohan Yu, Jinmiao Cong, Shengzhi Wang +2
A key challenge in multi-agent reinforcement learning (MARL) lies in designing learning signals that effectively promote coordination among agents. Designing such signals requires…
cs.LG2026
PA-RNet: Perturbation-Aware Residual Network for Robust Multimodal Time Series Forecasting
Enqiang Zhu, Zhenbin Deng, Shengzhi Wang +2
In real-world applications, multimodal time-series forecasting faces a key challenge: textual information is often useful but unreliable. Auxiliary texts may contain irrelevant, am…
cs.CL2025
DP-GPT4MTS: Dual-Prompt Large Language Model for Textual-Numerical Time Series Forecasting
Chanjuan Liu, Shengzhi Wang, Enqiang Zhu
Time series forecasting is crucial in strategic planning and decision-making across various industries. Traditional forecasting models mainly concentrate on numerical time series d…