lmms-lab/FVQA

Factual Visual Question Answering (FVQA) Dataset Summary FactualVQA (FVQA) is a multimodal Visual Question Answering dataset created for search-augmented training and evaluation. It emphasizes knowledge-intensive questions that require external information beyond the given image. Each entry includes an image, a question, and an answer (optionally accompanied by candidate answers), enabling models to develop and refine on-demand search strategies. Details of dataset… See the full description on the dataset page: https://huggingface.co/datasets/lmms-lab/FVQA.

<iframe src="https://silytics.si/embed/item/8dbfb1bb-2ae3-4a68-976e-9e02a8c78c7d" width="420" height="190" style="border:0" loading="lazy" title="Silytics entry"></iframe>

Silytics shows public metadata from Hugging Face and links to the original. Information may be incomplete or out of date. Last refreshed 14 October 2026. Licenses and terms of the original apply to the work itself. Not financial, legal or professional advice.