The October 2, 2025 technical report from Tencent AI Lab introduces CLUE (Clustering and Experience-based Verification), a novel, non-parametric method for assessing the correctness of solutions generated by Large Language Models (LLMs). The authors argue that a solution's quality is geometrically encoded in the LLM's internal hidden state trajectories, specifically using the activation delta (the difference in hidden states before and after the reasoning block) as a robust signal. CLUE is a training-free approach that establishes success and failure centroids from past labeled experience and classifies new solutions by their proximity to these clusters. Empirical results demonstrate that CLUE significantly outperforms traditional LLM-as-a-judge and confidence-based baselines in both binary classification and solution reranking across mathematical and general reasoning benchmarks. The research highlights that models fine-tuned with Reinforcement Learning (RL) exhibit superior geometric separation of correct and incorrect reasoning, making them inherently stronger verifiers. Source: https://arxiv.org/pdf/2510.01591