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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4.2 Abstractive Question Answering
- How did RAG do on MS-MARCO NLG without the gold passages?RAG-Sequence beat BART by 2.6 BLEU and 2.6 ROUGE-L and approached systems that use the gold passages, hallucinating less and producing factually correct text more often.
- Lewis et al., 2020, Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks (Advances in Neural Information Processing Systems 33 (NeurIPS 2020)), §4.2
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