Papers with GenFuser

1 papers
LLM-Blender: Ensembling Large Language Models with Pairwise Ranking and Generative Fusion (2023.acl-long)

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Challenge: a recent study shows that open-source large language models (LLMs) exhibit diverse strengths and weaknesses due to variations in their architectures and training data.
Approach: They propose a framework that leverages the diverse strengths of open-source large language models.
Outcome: The proposed framework outperforms individual LLMs and baseline methods across various metrics, establishing a substantial performance gap.

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