Jiarui Yu

Reinforcement Learning with Verifiable Rewards (RLVR) serves as a cornerstone technique for enhancing the reasoning capabilities of Large Language Models (LLMs). However, its training is often plagued by entropy collapse , a rapid decline in policy entropy that limits exploration and undermines t...

Recently, latent reasoning has been introduced into large language models (LLMs) to leverage rich information within a continuous space.However, without stochastic sampling, these methods inevitably collapse to deterministic inference, failing to discover diverse reasoning paths.To bridge the gap...