Rethinking Search: Making Experts out of Dilettantes

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Survey of Hallucination in Natural Language Generation (2022, methodology): “A GQA system can be integrated with a search engine [129] to empower more intelligent search or combined with a virtual conversation agent to enhance user experience.”
Dense Text Retrieval Based on Pretrained Language Models: A Survey (2022, methodology): “Specially, the perspective paper [297] envisions the model-based paradigm that simplifies the classic index-retrieve-then-rank paradigm by a unified relevance model.”
Read before Generate! Faithful Long Form Question Answering with Machine Reading (2022, background): “It can be integrated with a search engine (Metzler et al., 2021), or a virtual conversation agent, and can also be used to generate explanations as a complement to short-phrase answers for open-domain questions (Kwiatkowski et al., 2019; Yang et al., 2018), or to answer open-ended questions like…”
RocketQAv2: A Joint Training Method for Dense Passage Retrieval and Passage Re-ranking (2021, background): “Therefore, there is increasing attention on correlating the training of the retriever and re-ranker in order to achieve mutual improvement (Metzler et al., 2021; Qu et al., 2021; Huang et al., 2020; Yang et al., 2020).”