PromptBench introduces a unified library to simplify and standardize the process of evaluating Large Language Models (LLMs). Various components like prompt construction and engineering, dataset and model loading, along with adversarial prompt attack mechanisms, come together in this library. This flexible toolset is designed to support the creation of new benchmarks, deploy downstream applications, and devise new evaluation protocols for LLMs.

Key features outlined in the paper:

• A unified library of tools for LLM evaluation.
• An open-source codebase that facilitates extension and customization.
• A diverse array of tools including adversarial prompt attacks and dynamic evaluations.
• Continuous support for the library to encourage community involvement and contributions.

This work is crucial as it empowers researchers with a robust set of tools facilitating accurate and comprehensive LLM assessments. It is poised to become a valuable asset for the AI research community, fostering innovation in LLM development and application. Discover more about PromptBench.