Tian Liang

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cs.LG2026

From $P (y ∣ x)$ to $P (y)$ : Investigating Reinforcement Learning in Pre-train Space

Yuqiao Tan, Minzheng Wang, Bo Liu +5

While reinforcement learning with verifiable rewards (RLVR) significantly enhances LLM reasoning by optimizing the conditional distribution P(y|x), its potential is fundamentally b…

cs.LG2025

Bottom-up Policy Optimization: Your Language Model Policy Secretly Contains Internal Policies

Yuqiao Tan, Minzheng Wang, Shizhu He +6

Existing reinforcement learning (RL) approaches treat large language models (LLMs) as a unified policy, overlooking their internal mechanisms. In this paper, we decompose the LLM-b…

From P(y∣x) to P(y): Investigating Reinforcement Learning in Pre-train Space

Bottom-up Policy Optimization: Your Language Model Policy Secretly Contains Internal Policies

From $P (y ∣ x)$ to $P (y)$ : Investigating Reinforcement Learning in Pre-train Space