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cs.CL2025
Diverse LLMs or Diverse Question Interpretations? That is the Ensembling Question
Rafael Rosales, Santiago Miret
Effectively leveraging diversity has been shown to improve performance for various machine learning models, including large language models (LLMs). However, determining the most ef…
cs.CL2022★ 1 cited
Can Retriever-Augmented Language Models Reason? The Blame Game Between the Retriever and the Language Model
Parishad BehnamGhader, Santiago Miret, Siva Reddy
Augmenting pretrained language models with retrievers has shown promise in effectively solving common NLP problems, such as language modeling and question answering. In this paper,…