Author

Shi-Jie Li

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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

Preprint Aug 2026

MAG: MAnifold Guided Semi-Supervised Multi-modal In-Context Learning

Few-shot in-context learning (ICL) with multi-modal large language models (MLLMs) enables task adaptation without parameter updates, but its performance is highly sensitive to the quality and coverage of the selected demonstrations. While unlabeled multi-modal data is abundant, it remains elusive how to exploit them fo...

Zirui Cheng, Xun Xu, Tiankai Chen et al. · 0 citations