Can Vendi-RAG maintain answer accuracy on the HotpotQA benchmark when the diversity weight hyperparameter is s

Abstract

Abstract: Large Language Models (LLMs) have drawn a lot of attention due to their strong performance on a wide range of natural language tasks, since the release of ChatGPT in November 2022. LLMs' ability of general-purpose language understanding and generation is acquired by training billions of model's parameters on massive amounts of text data, as predicted by scaling laws cite\kaplan2020scaling,hoffmann2022training\. The research area of LLMs, while very recent, is evolving rapidly in many different ways. In this paper, we review some of the most prominent LLMs, including three popular LLM families

Research Question

Can Vendi-RAG maintain answer accuracy on the HotpotQA benchmark when the diversity weight hyperparameter is scaled across a range of 0.1 to 1.0, measured against the Tree of Reviews evaluation metric?

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