Jiasheng Li

Calibrate Before Reason: Robust Visual Token Reduction against Semantic Drift in VLMs

CaRe is proposed, a training-free robust framework that calibrates compact visual representations before reasoning to preserve semantic fidelity in VLMs and outperforms state-of-the-art token reduction baselines.