Nina Montaña-Brown

Balancing Act: Diversity and Consistency in Large Language Model Ensembles

Ensembling strategies for Large Language Models (LLMs) have demonstrated significant potential in improving performance across various tasks by combining the strengths of individual models. However, identifying the most effective ensembling method remains an open challenge, as neither maximizing out…