Yixin Zhang

Toward fairer large language models: a divergence-reflection-convergence framework for mitigating cognitive bias

Purpose Cognitive bias in large language models (LLMs) undermines their reliability due to the practical limitations of existing mitigation methods. This study introduces a divergence-reflection-convergence (DRC) framework, which leverages a computationally efficient and inferenc...