HarvardVCG/MisVisBench
Evaluating Vision-Language Models on Misleading Data Visualizations (Dataset) Overview This dataset accompanies the paper: “When Visuals Aren’t the Problem: Evaluating Vision-Language Models on Misleading Data Visualizations.” MisVisBench is designed to evaluate whether Vision-Language Models (VLMs) can detect misleading information in data visualization-caption pairs, and whether they can correctly attribute the source of misleadingness to appropriate error… See the full description on the dataset page: https://huggingface.co/datasets/HarvardVCG/MisVisBench.
| Author / organization | HarvardVCG |
|---|---|
| License (as declared) | cc-by-nc-sa-4.0 |
| Downloads | 231 (as reported by Hugging Face) |
| Likes | 1 |
| Created | 24 March 2026 |
| Last updated at source | 7 August 2026 |
Popularity, last 2 days
231 now (-5 since 2026-10-16). Counts as reported by the source, snapshotted daily by Silytics.
Related papers
Silytics shows public metadata from Hugging Face and links to the original. Information may be incomplete or out of date. Last refreshed 17 October 2026. Licenses and terms of the original apply to the work itself. Not financial, legal or professional advice.