[D] In the paper "More Agents Is All You Need", why did they use BLEU score to calculate similarity for ensemble voting instead of something like cosine similarity? Has there been any follow-up research comparing methods?

Paper: [https://arxiv.org/pdf/2402.05120.pdf](https://arxiv.org/pdf/2402.05120.pdf)

In the paper, they have ensembles of LLMs answer questions. For discrete answers, like multiple choice questions, they just pick the most frequent answer. For "continuous" answers like code, they use BLEU score to find the answer that is the most similar to others.

Does anyone have insight on why that was chosen over something like cosine similarity? It doesn't look like they explain the choice, but their results are good so I guess it worked!

bleu code continuous cosine insight llms machinelearning multiple paper questions something