August 17, 2025InformationOpen Access

Ensemble Large Language Models: A Survey

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This review explores ensemble learning in large language models, addressing performance issues and highlighting potential advancements.

Ensemble learning improves performance and robustness in large language models, addressing critical challenges in NLP.
The analysis evaluates methodologies and applications across diverse domains, revealing strengths and limitations in existing models.
Ensemble strategies can enhance generalizability and interpretability, indicating a significant shift in natural language processing approaches.
Potential future research directions aim to further optimize ensemble methods for large language models and tackle existing biases.

Mienye et al. (2025) studied this question.

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