Seven Failure Points When Engineering a Retrieval Augmented Generation System-Reference-Cited by-同舟云学术

Seven Failure Points When Engineering a Retrieval Augmented Generation System

Published:2024-04-14 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the IEEE/ACM 3rd International Conference on AI Engineering - Software Engineering for AI
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Author:

Barnett Scott¹^ORCID,Kurniawan Stefanus¹^ORCID,Thudumu Srikanth¹^ORCID,Brannelly Zach¹^ORCID,Abdelrazek Mohamed¹^ORCID

Affiliation:

1. Applied Artificial Intelligence Institute, Deakin University, Victoria, Australia

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3644815.3644945

Reference18 articles.

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3. Jiawei Chen, Hongyu Lin, Xianpei Han, and Le Sun. 2023. Benchmarking Large Language Models in Retrieval-Augmented Generation. arXiv preprint arXiv:2309.01431 (2023).

4. Mingda Chen, Xilun Chen, and Wen-tau Yih. 2023. Efficient Open Domain Multi-Hop Question Answering with Few-Shot Data Synthesis. arXiv preprint arXiv:2305.13691 (2023).

5. Threshy: supporting safe usage of intelligent web services

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