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cs.LG2026
Align and Filter: Improving Performance in Asynchronous On-Policy RL
Homayoun Honari, Roger Creus Castanyer, Michael Przystupa +3
Distributed training and increasing the gradient update frequency are practical strategies to accelerate learning and improve performance, but both exacerbate a central challenge:…
cs.LG2025
A Comedy of Estimators: On KL Regularization in RL Training of LLMs
Vedant Shah, Johan Obando-Ceron, Vineet Jain +10
The reasoning performance of large language models (LLMs) can be substantially improved by training them with reinforcement learning (RL). The RL objective for LLM training involve…