Author

Shiu-hong Kao

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Preprint Sep 2026

Aligning Thoughts with Answers: Probability Rewards to Tame Thinking Drift

This paper studies \textbf{thinking--answer consistency} in vision-language models. We focus on Visual Intention Grounding, where a model infers a target object based on a human intention query and predicts a bounding box. We reveal that previous IoU-based reinforcement learning (RL) frameworks suffer from ``thinking d...

Peng-Zhan Sun, Shiu-hong Kao, Shi-Jie Li et al. · 1 citation

#artificial intelligence Preprint Oct 2026

Rethinking Probability-Based Reinforcement Learning From Posterior Concentration

Verifier-free reinforcement learning with probability-based rewards offers a promising way to train LLMs on general reasoning tasks where external verifiers are unavailable. Yet the reliability of these rewards, especially in long-horizon reasoning, remains underexplored. This work identifies a length-dependent failure...

Shiu-hong Kao, Yu-Bo Zhao, Zhen Tian et al. · 0 citations