Augmenting language models with a retrieval mechanism has been shown to significantly improve their performance while keeping the number of parameters low.

May 25, 2023 · In this paper, we study the state-of-the-art Retro model and observe that its performance gain is better explained by surface-level similarities, such as token ...

Jul 9, 2023 · Retrieval-augmented models commonly rely on a semantic retrieval mechanism based on the similarity between dense representations of the query ...

Retrieval-augmented models commonly rely on a semantic retrieval mechanism based on the similarity between dense representations of the query chunk and.

Those works believe that the concatenated/fused retrievals can provide useful context information on inputs/outputs to improve models' robustness during the ...

This repository contains the code for Surface-Based Retrieval Reduces Perplexity of Retrieval-Augmented Language Models. For setting up the environment, ...

Augmenting language models with a retrieval mechanism has been shown to significantly improve their performance while keeping the number of parameters low.

Apr 16, 2024 · Retrieval-augmented language models pose a promising alternative to standard language modeling. During pretraining, these models.

Inspired by this, we replace the semantic retrieval in Retro with a surface-level method based on BM25, obtaining a significant reduction in perplexity. 1.

This repository is dedicated to curating high-quality papers, resources, and tools related to RAG in the context of Large Language Models (LLM).