#self-bias News & Analysis

When LLMs Benchmark Themselves: Deconstructing Self-Bias in Automated Evaluation

A research paper reveals that large language models used to create and evaluate benchmarks systematically favor themselves, introducing significant bias into automated evaluation systems. The self-bias stems from both test generation and evaluation stages, with stylistic tendencies creating model-specific outputs that inflate scores, even when diversity controls are explicitly applied.