VQA-X

The 'VQA-X' dataset is used to evaluate the faithfulness of natural language explanations generated by vision-language models in the context of visual question answering tasks.

Papers using VQA-X (4)

On Advances in Text Generation from Images Beyond Captioning: A Case Study in Self-Rationalization2022Benchmarking Faithfulness: Towards Accurate Natural Language Explanations in Vision-Language Tasks2023From Wrong To Right: A Recursive Approach Towards Vision-Language Explanation2023Cross-Lingual Text-Rich Visual Comprehension: An Information Theory Perspective2024