UCSC-VLAA/vllm-safety-benchmark
[ECCV 2024] Official PyTorch Implementation of "How Many Unicorns Are in This Image? A Safety Evaluation Benchmark for Vision LLMs"
This project helps AI researchers and developers evaluate the safety and robustness of their Vision-Language Models (VLLMs). It takes a VLLM and a variety of challenging image and text datasets as input, then measures how well the VLLM handles out-of-distribution scenarios and red-teaming attacks. The output provides quantifiable metrics on a VLLM's safety performance, helping identify vulnerabilities before deployment.
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Use this if you are developing or deploying Vision-Language Models and need to rigorously assess their behavior and safety under challenging and adversarial conditions.
Not ideal if you are looking for a general-purpose VLLM or a tool to generate adversarial attacks without a focus on safety benchmarking.
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Nov 28, 2023
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