When AI Benchmarks Plateau: A Systematic Study of Benchmark Saturation 事件

When AI Benchmarks Plateau: A Systematic Study of Benchmark Saturation arXiv:2602.16763v2 Announce Type: replace Abstract: Artificial intelligence benchmarks are an important mechanism for measuring model progress and guiding deployment decisions. However, benchmarks quickly "saturate", making it difficult to differentiate models and diminishing their long-term value. In this study, we define benchmark saturation and analyze it across 60 language model benchmarks using 14 properties that relate