GAVEL: Grounded Caption Error Verification and Localization
Vision-language models (VLMs) often produce hallucinated or inconsistent outputs, where text and images are not properly aligned. Addressing this issue requires not only detecting misalignment but also explaining the discrepancy and localizing its visual evidence. We introduce GAVEL (Grounded Caption Error Verification and Localization), a task that jointly addresses verification, explanation, and localization for image-text pairs. To support systematic evaluation, we also present a corresponding dataset and benchmark. We further train a supervised baseline on the human-annotated training split to assess whether GAVEL provides learnable supervision for these abilities. Experiments show th...
| Authors | Zixian Gao, Atsushi Hashimoto, Kuniaki Saito |
|---|---|
| Primary category | cs.CL |
| Published | 25 June 2026 |
| Last updated at source | 25 June 2026 |
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