3 papers
cs.LG2026
Follow the Winners: Conservative Policy Improvement with the Cross-Entropy Method for Critic-Free RFT
Joery Ariën de Vries, Neil David Lawrence, Zhenwen Dai
Critic-free reinforcement fine-tuning (RFT) for agentic large language models is often done through GRPO-style methods, which compute a group baseline over repeated rollouts to red…
cs.LG2026
Particle Monte Carlo Tree Search
Yaniv Oren, Viliam Vadocz, Joery A. de Vries +3
Monte Carlo Tree Search (MCTS) is a widely used approach for policy improvement and action selection in Reinforcement Learning. Due to its sequential and deterministic nature, prin…
cs.LG2025
Twice Sequential Monte Carlo for Tree Search
Yaniv Oren, Joery A. de Vries, Pascal R. van der Vaart +2
Model-based reinforcement learning (RL) methods that leverage search are responsible for many milestone breakthroughs in RL. Sequential Monte Carlo (SMC) recently emerged as an alt…