Author

Gal Chechik

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Preprint Oct 2026

Look Where You Say You're Looking: Self-Grounded Attention for Visual Reasoning

We introduce Self-Saliency, a method for training Vision-Language Models (VLMs) to increase the alignment between their visual attention and the image regions mentioned in their reasoning. Self-Saliency uses a grounding model to localize the objects mentioned in each reasoning step and treats the resulting areas as sup...

Uri Berger, Gal Chechik, Gal Dalal · 1 citation

Preprint Aug 2026

UniProbe: A Learnable Token-Level Hallucination Detector for Large VLMs using Multi-Structural Internal Representations

UniProbe is introduced, a lightweight, unified, learnable detector that models a frozen LVLM's heterogeneous computational trace from a single forward pass and achieves state-of-the-art token-level and object-hallucination detection.

Dvir Samuel, Guy Bar-Shalom, Fabrizio Frasca et al. · 0 citations