AI article
Test-Time Compute and GRPO in Practice: From PPO to Critic-Free Reinforcement Learning
Community description: A deep dive into the paradigm shift from pre-training scaling laws to test-time compute. We deconstruct the mathematical derivation of DeepSeek-R1's Group Relative Policy Optimization (GRPO), critic-free architecture advantages, emergent self-reflection in long reasoning traces, and a complete, reproducible hands-on implementation.
Dev.to | Sep 20, 2026 | ifnodoraemon
Automated excerpt
Process Reward Models (PRMs) score intermediate steps within tree search (Beam Search / MCTS). Actor Model ($\pi_\theta$): The trainable policy generating tokens. Reward Model ($R_\psi$): A frozen network scoring terminal outputs.
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