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When Seeing Is Not Enough: Benchmarking Interactive Visual Grounding in LVLMs

arXiv · AI, language, vision and robotics · article · Aug 25, 2026 · UTC

Visual grounding is typically evaluated as a one-shot mapping from an informative referring expression to a visual target. This formulation misses a central property of real-world reference: initial referring expressions are often incomplete or ambiguous, requiring participants to establish shared understanding through interaction. We introduce a controlled evaluation framework for interactive visual grounding in large vision-language models (LVLMs), varying how much target information is provided upfront and how much must be acquired through dialogue. Across four human-grounded visual context

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