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cs.LG2025
Self-Guided Process Reward Optimization with Redefined Step-wise Advantage for Process Reinforcement Learning
Wu Fei, Hao Kong, Shuxian Liang +5
Process Reinforcement Learning~(PRL) has demonstrated considerable potential in enhancing the reasoning capabilities of Large Language Models~(LLMs). However, introducing additiona…
cs.LG2024
Progressive Neural Network for Multi-Horizon Time Series Forecasting
Yang Lin
In this paper, we introduce ProNet, an novel deep learning approach designed for multi-horizon time series forecasting, adaptively blending autoregressive (AR) and non-autoregressi…