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readme.md

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[![arXiv](https://img.shields.io/badge/arxiv-2402.15429-red)](https://arxiv.org/abs/2402.15429)
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[![poster]()
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> [Yi Zhang](https://scholar.google.com/citations?user=9E8XJ54AAAAJ&hl=en), [Xingyu Zhao*](https://scholar.google.com/citations?user=SzEBdA8AAAAJ&hl=en), [Yun Tang](https://scholar.google.com/citations?hl=en&user=idlExzkAAAAJ), [Wenjie Ruan](https://scholar.google.com/citations?user=VTASFGEAAAAJ&hl=en),
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[Xiaowei Huang](https://scholar.google.com/citations?user=X4fLCCIAAAAJ&hl=en),
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[Siddartha Khastgir](https://scholar.google.com/citations?hl=en&user=r3ldU6sAAAAJ),
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[Paul Jennings](https://scholar.google.com/citations?hl=en&user=HOVIdYwAAAAJ)
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>
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> *Corresponding Author
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We propose an efficient framework, ProTIP, to evaluate the probabilistic robustness of Text-to-Image diffusion model with statistical guarantees.
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## Overview
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<p align="center">

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