LLM Evaluation Benchmarks: Combating Data Contamination with Dynamic Techniques

12 hours ago 高效码农

Recent Advances in Large Language Model Benchmarks Against Data Contamination: From Static to Dynamic Evaluation Image: Original project file Central Question of This Article Why has data contamination become such a pressing issue for large language models, and how has benchmarking evolved from static methods to dynamic approaches to address it? This article provides a comprehensive walkthrough of the evolution of benchmarking for large language models (LLMs), focusing on the shift from static benchmarks toward dynamic evaluation. It explains what data contamination is, why it matters, how different benchmarks are designed, and where current methods succeed or fall short. Along …