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🚀 Happy to present our work: Asymmetric Proximal Policy Optimization: Mini-Critics Boost LLM Reasoning. We re-examine PPO in LLM domain and find 3 key insights:
👀 (1) The critic might serve as a natural safeguard for stable policy training.
⚡️ (2) Training smarter reasoning agents does not require a giant critic—value estimation capability is not equivalent to model size.
😮 (3) Critic signals can further guide the reconstruction of the policy loss objective itself.
I'll go step-by-step through this thread👇.

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