Overview - Retrieval-Augmented Generation 2024

Proceedings | Data | Results | Runs | Participants

The (TREC) Retrieval-Augmented Generation Track is intended to foster innovation and research within the field of retrieval-augmented generation systems. This area of research focuses on combining retrieval methods - techniques for finding relevant information within large corpora with Large Language Models (LLMs) to enhance the ability of systems to produce relevant, accurate, updated and contextually appropriate content.

Track coordinator(s):

• Ronak Pradeep, University of Waterloo
• Nandan Thakur, University of Waterloo
• Jimmy Lin, University of Waterloo
• Nick Craswell, Microsoft

Tasks:

• retrieve: Retrieval
• auggen: Augmented Generation
• gen: Generation

Track Web Page: https://trec-rag.github.io

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