Structuring Prompts for Accessing Knowledge Stores
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Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks, Patrick Lewis, Ethan Perez, Aleksandra Piktus, Fabio Petroni, Vladimir Karpukhin, Naman Goyal, Heinrich Küttler, Mike Lewis, Wen-tau Yih, Tim Rocktäschel, Sebastian Riedel, Douwe Kiela, 2020Advances in Neural Information Processing Systems (NeurIPS)DOI: 10.48550/arXiv.2005.11401 - This paper introduces Retrieval-Augmented Generation (RAG), a framework that combines pre-trained parametric and non-parametric memory to enable models to access and utilize external knowledge, forming the basis for many knowledge store interaction patterns.
Toolformer: Language Models That Can Use Tools, Timo Schick, Jane Dwivedi-Yu, Roberto Dessì, Roberta Raileanu, Maria Lomeli, Luke Zettlemoyer, Nicola Cancedda, Thomas Scialom, 2023arXiv preprint arXiv:2302.04761DOI: 10.48550/arXiv.2302.04761 - This paper introduces Toolformer, an approach for teaching language models to use external tools via self-supervised learning, demonstrating how models can learn to call APIs and integrate their outputs.
ReAct: Synergizing Reasoning and Acting in Language Models, Shunyu Yao, Jeffrey Zhao, Dian Yu, Nan Du, Izhak Shafran, Karthik Narasimhan, Yuan Cao, 2023arXiv preprint arXiv:2210.03629DOI: 10.48550/arXiv.2210.03629 - This paper proposes ReAct, a general paradigm for language models to perform reasoning and take action, which includes interacting with external tools and knowledge bases by interleaving thinking and acting steps.
Prompt Engineering Guide, Shubham Kumar, et al., 2023 - This comprehensive online guide covers various prompt engineering techniques, including those for tool use, agent design, and interacting with external systems, offering practical examples and best practices.