In authors or contributors

1 resource

  • Jon Saad-Falcon, Omar Khattab, Christoph...
    |
    Mar 31st, 2024
    |
    preprint
    Jon Saad-Falcon, Omar Khattab, Christoph...
    Mar 31st, 2024

    Evaluating retrieval-augmented generation (RAG) systems traditionally relies on hand annotations for input queries, passages to retrieve, and responses to generate. We introduce ARES, an Automated RAG Evaluation System, for evaluating RAG systems along the dimensions of context relevance, answer faithfulness, and answer relevance. By creating its own synthetic training data, ARES finetunes lightweight LM judges to assess the quality of individual RAG components. To mitigate potential...

Last update from database: 27/12/2024, 16:15 (UTC)
Powered by Zotero and Kerko.