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cs.LG2026
Efficient Resource-Shiftable RL Post-training with Generative Rewards
Yanfeng Zhao, Haoyang Li, Sheng Lin +4
Reinforcement learning (RL) post-training with generative reward models (GenRM) has become a central recipe for improving large language models (LLMs), and it is also increasingly…
cs.LG2026
Perceive, Route and Modulate: Dynamic Pattern Recalibration for Time Series Forecasting
Siru Zhong, Zhao Meng, Haohuan Fu +3
Local temporal patterns in real-world time series continuously shift, rendering globally shared transformations suboptimal. Current deep forecasting models, despite their scale and…