LLM Evaluation

Evaluating large language models (LLMs) focuses on establishing their reliability, safety, and suitability for various applications. Current research emphasizes developing robust and comprehensive evaluation frameworks, moving beyond simple accuracy metrics to assess aspects like data privacy, bias, explainability, and the ability to combine different skills. This rigorous evaluation is crucial for responsible LLM development and deployment, informing both the scientific understanding of these models and their safe integration into real-world applications across diverse fields.