@inproceedings{lee-lee-2026-toxiprompt,
    title = "{T}oxi{P}rompt: A Two-Stage Red-Teaming Approach for Balancing Adversarial Prompt Diversity and Response Toxicity",
    author = "Lee, Seungho  and
      Lee, Kyumin",
    editor = "Demberg, Vera  and
      Inui, Kentaro  and
      Marquez, Llu{\'i}s",
    booktitle = "Proceedings of the 19th Conference of the {E}uropean Chapter of the {A}ssociation for {C}omputational {L}inguistics (Volume 1: Long Papers)",
    month = mar,
    year = "2026",
    address = "Rabat, Morocco",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/manual-author-scripts/2026.eacl-long.170/",
    pages = "3682--3696",
    ISBN = "979-8-89176-380-7",
    abstract = "While large language models (LLMs) offer great promise, they also pose concrete safety risks. To audit and mitigate these risks, researchers have developed automated red-teaming methods, which generate adversarial prompts to elicit unsafe behavior of target LLMs during evaluation. Recent automated red-teaming methods for LLMs face a persistent trade-off: techniques that increase prompt diversity often reduce the level of the toxicity elicited from the target LLMs, while toxicity-maximizing methods tend to collapse diversity. To address the limitations, we propose ToxiPrompt, a two-stage framework that explicitly separates exploration (diversity) from exploitation (toxicity) and reunifies them with a single selection criterion to balance between diversity and toxicity. Experimental results show that ToxiPrompt outperforms four state-of-the-art baselines in both adversarial prompt diversity and the level of elicited toxicity from target LLMs, improving 14.6{\%} harmonic mean of toxicity and diversity against the best baseline. The approach also performs well for multiple instruction-tuned target LLMs (Llama-2/3, Qwen, Mistral) without re-tuning, achieving up to 55{\%} harmonic mean improvement against the best baseline. Our code is available at https://github.com/seungho715/ToxiPrompt"
}