GAVEL: Grounded Caption Error Verification and Localization
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Computer Science > Computation and Language
Title:GAVEL: Grounded Caption Error Verification and Localization
Abstract: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 that even strong closed-source models struggle on GAVEL, while the supervised baseline yields consistent improvements across grounding and explanation metrics.
| Comments: | conference |
| Subjects: | Computation and Language (cs.CL) |
| Cite as: | arXiv:2606.26923 [cs.CL] |
| (or arXiv:2606.26923v1 [cs.CL] for this version) | |
| https://doi.org/10.48550/arXiv.2606.26923
arXiv-issued DOI via DataCite (pending registration)
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