2 papers
cs.CL2026
ToxiGAN: Toxic Data Augmentation via LLM-Guided Directional Adversarial Generation
Peiran Li, Jan Fillies, Adrian Paschke
Augmenting toxic language data in a controllable and class-specific manner is crucial for improving robustness in toxicity classification, yet remains challenging due to limited su…
cs.CR2025
SIRAJ: Diverse and Efficient Red-Teaming for LLM Agents via Distilled Structured Reasoning
Kaiwen Zhou, Ahmed Elgohary, A S M Iftekhar +1
The ability of LLM agents to plan and invoke tools exposes them to new safety risks, making a comprehensive red-teaming system crucial for discovering vulnerabilities and ensuring…