Online Safety Analysis for Large Language Models: Benchmarking, Evaluation, and Future Directions

Developing effective online safety analysis methods for Large Language Models (LLMs) is crucial to ensure their trustworthy and reliable deployment across diverse domains. This work establishes a comprehensive benchmark to systematically evaluate the performance of existing online safety analysis techniques on both open-source and closed-source LLMs, providing valuable insights for future advancements in this field.