Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks
Lewis et al., 2020, Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks (Advances in Neural Information Processing Systems 33 (NeurIPS 2020))
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3 Experiments
- What non-parametric memory did RAG use?A December 2018 Wikipedia dump split into disjoint 100-word chunks, 21M passages, embedded by the DPR document encoder and indexed with FAISS (HNSW approximation); 5 or 10 documents were retrieved per query in training.
- Lewis et al., 2020, Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks (Advances in Neural Information Processing Systems 33 (NeurIPS 2020)), §3
Source
- Patrick Lewis, Ethan Perez, Aleksandra Piktus, Fabio Petroni, Vladimir Karpukhin, Naman Goyal, Heinrich Küttler, Mike Lewis, Wen-tau Yih, Tim Rocktäschel, Sebastian Riedel and Douwe Kiela. 2020. Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks. In Advances in Neural Information Processing Systems 33 (NeurIPS 2020). https://papers.nips.cc/paper/2020/hash/6b493230205f780e1bc26945df7481e5-Abstract.html