koenshen/EVADE-Bench

EVADE-Bench: Multimodal Benchmark for Evaluating and Enhancing Evasive Content Detection 🤗 Dataset | Paper | GitHub E-commerce platforms increasingly rely on Large Language Models and Vision-Language Models to detect illicit or misleading product content. However, these models remain vulnerable to evasive content, which refers to inputs that superficially comply with platform policies while covertly conveying prohibited claims. Unlike traditional adversarial attacks that aim to… See the full description on the dataset page: https://huggingface.co/datasets/koenshen/EVADE-Bench.

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