Resolution Thresholds in VLM Detection of Harmful ASCII Art Across Construction Modes and Languages
Large Vision-Language Models (VLMs) are increasingly deployed as content moderation tools, yet they remain vulnerable to jailbreak attacks in which harmful text is visually encoded as ASCII art. This can allow inappropriate or harmful content to bypass moderation systems. To address this vulnerability, this paper investigates how image resolution affects VLM detection of harmful ASCII art across eight character construction modes (L1-L8), ranging from dense block characters to word-embedded designs. We evaluate eight state-of-the-art VLMs on English and Chinese corpora using a pipeline that generates ASCII art images at ten resolution scales, probing whether a consistent detection-failure...
| Authors | Yikai Hua, Peter West |
|---|---|
| Primary category | cs.CL |
| Published | 28 June 2026 |
| Last updated at source | 28 June 2026 |
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