Papers by Arijit Ray

2 papers
Sunny and Dark Outside?! Improving Answer Consistency in VQA through Entailed Question Generation (D19-1)

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Challenge: interacting with a model for Visual Question Answering (VQA) quickly reveals that these models lack consistency.
Approach: They propose a dataset, ConVQA, and metrics that enable quantitative evaluation of consistency in VQA.
Outcome: The proposed data augmentation module improves the consistency of VQA models on the Con-VQA dataset and is a strong baseline for future research.
BloomVQA: Assessing Hierarchical Multi-modal Comprehension (2024.findings-acl)

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Challenge: Recent advances of machine intelligence solutions have demonstrated tremendous success in a wide range of language and multi-modal tasks over diverse domains.
Approach: They propose a VQA dataset to facilitate comprehensive evaluation of large vision-language models on comprehension tasks.
Outcome: The proposed dataset shows improved accuracy over all comprehension levels and a tendency to bypass visual inputs especially for higher-level tasks.

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