Monosail/HADES
Overview The HADES benchmark is derived from the paper "Images are Achilles' Heel of Alignment: Exploiting Visual Vulnerabilities for Jailbreaking Multimodal Large Language Models" (ECCV 2024 Oral). You can use the benchmark to evaluate the harmlessness of MLLMs. Benchmark Details HADES includes 750 harmful instructions across 5 scenarios, each paired with 6 harmful images generated via diffusion models. These images have undergone multiple optimization rounds… See the full description on the dataset page: https://huggingface.co/datasets/Monosail/HADES.
| Author / organization | Monosail |
|---|---|
| License (as declared) | mit |
| Downloads | 304 (as reported by Hugging Face) |
| Likes | 1 |
| Created | 25 September 2024 |
| Last updated at source | 17 October 2024 |
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- 16 Oct 2026 Description: Overview The HADES benchmark is derived from the paper "Images are Achilles' Heel of Alignment: Exploiting Visual Vulnerabilities for Jailbreaking Multimodal Large Language Models" (ECCV 2024 Oral). You can use the benchmark to evaluate the → Overview The HADES benchmark is derived from the paper "Images are Achilles' Heel of Alignment: Exploiting Visual Vulnerabilities for Jailbreaking Multimodal Large Language Models" (ECCV 2024 Oral). You can use the benchmark to evaluate the
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