Papers by Xinchi XU
VL-Calibration: Decoupled Confidence Calibration for Large Vision-Language Models Reasoning (2026.acl-long)
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| Challenge: | Existing verbalized confidence calibration methods for large vision language models optimize a single holistic confidence score using binary answer-level correctness. |
| Approach: | They propose a reinforcement learning framework that explicitly decouples confidence into visual and reasoning confidence. |
| Outcome: | Experiments show that the proposed framework decouples confidence into visual and reasoning confidence while suppressing ungrounded hallucinations while preserving valid perception. |