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Despite the significant progress made by existing retrieval augmented language models (RALMs) in providing trustworthy responses and grounding in reliable sources, they often overlook effective alignment with human preferences.
Rank analysis of incomplete block designs: I. the method of paired comparisons
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Retrieval-augmented generation for knowledge-intensive NLP tasks
Patrick S. H. 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 · 2020
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RobustQA: Benchmarking the robustness of domain adaptation for open-domain question answering
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Privacy implications of retrieval-based language models
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Camels in a changing climate: Enhancing LM adaptation with tulu 2
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Atlas: Few-shot learning with retrieval augmented language models
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