longlian/VPBench
VPBench: Visually Prompted Benchmarks Are Surprisingly Fragile Project Page | Paper | GitHub VPBench is a benchmark designed to evaluate the robustness of Vision-Language Models (VLMs) to visual prompting. As detailed in the paper "Visually Prompted Benchmarks Are Surprisingly Fragile", existing models can be highly sensitive to seemingly irrelevant details such as marker color, size, and JPEG compression. VPBench curates existing datasets to create a larger benchmark with 16… See the full description on the dataset page: https://huggingface.co/datasets/longlian/VPBench.
| Author / organization | longlian |
|---|---|
| License (as declared) | cc-by-nc-4.0 |
| Downloads | 259 (as reported by Hugging Face) |
| Likes | 2 |
| Created | 9 January 2026 |
| Last updated at source | 16 January 2026 |
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- 17 Oct 2026 Description: VPBench: Visually Prompted Benchmarks Are Surprisingly Fragile Project Page | Paper | GitHub VPBench is a benchmark designed to evaluate the robustness of Vision-Language Models (VLMs) to visual prompting. As detailed in the paper "Visually → VPBench: Visually Prompted Benchmarks Are Surprisingly Fragile Project Page | Paper | GitHub VPBench is a benchmark designed to evaluate the robustness of Vision-Language Models (VLMs) to visual prompting. As detailed in the paper "Visually
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