VQA-Validation-Data: Visual Question Answering Benchmark

A validation dataset for the Visual Question Answering (VQA) task, published on Kaggle. The dataset likely contains image-question-answer pairs designed to test models' ability to answer questions about visual content. The specific number of samples, data source, and creation date are not provided in the available metadata.

Use Cases

• Benchmark a VQA model's performance on unseen data (inferred from domain, verify after download)
• Fine-tune a vision-language model on question-answer pairs (inferred from domain, verify after download)
• Analyze the types of questions and reasoning required for visual understanding (inferred from domain, verify after download)

Strengths

• Published on Kaggle, a major platform for data science and machine learning.
• Focuses on the established Visual Question Answering (VQA) task, a core multimodal benchmark.

Limitations

• Metadata is minimal; actual content requires verification after download.
• Row count, file formats, and column definitions are unknown, which limits suitability assessment.
• License, author, and last updated date are unknown.

Provenance

Source

Kaggle

Collection Method

Likely a subset or derivative of a standard VQA benchmark dataset.

Time Range

null

Freshness

Last updated date is unknown.

Geography

null