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cs.LG2026
Where to Spend Rollouts: Hit-Utility Optimal Rollout Allocation for Group-Based RLVR
Tao Wang, Shuo Li, Yan Sun +2
Reinforcement learning with verifiable rewards (RLVR) has emerged as a central paradigm for improving the reasoning capabilities of large language models. Group-based policy optimi…
cs.LG2026
The Forecast After the Forecast: A Post-Processing Shift in Time Series
Daojun Liang, Qi Li, Yinglong Wang +5
Time series forecasting has long been dominated by advances in model architecture, with recent progress driven by deep learning and hybrid statistical techniques. However, as forec…