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Although large language models (LLMs) have achieved significant success in various tasks, they often struggle with hallucination problems, especially in scenarios requiring deep and responsible reasoning.
Freebase: a collaboratively created graph database for structuring human knowledge
Kurt D. Bollacker, Colin Evans, Praveen K. Paritosh, Tim Sturge, and Jamie Taylor · 2008
Earlier work this paper cites.
Speech and language processing: an introduction to natural language processing, computational linguistics, and speech recognition, 2nd Edition
Dan Jurafsky and James H. Martin · 2009
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Semantic parsing on freebase from question-answer pairs
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Wikidata: A free collaborative knowledgebase
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Large-scale simple question answering with memory networks
Antoine Bordes, Nicolas Usunier, Sumit Chopra, and Jason Weston · 2015
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T-rex: A large scale alignment of natural language with knowledge base triples
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Alon Talmor and Jonathan Berant · 2018
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Roberta: A robustly optimized bert pretraining approach, 2019
Yinhan Liu, Myle Ott, Naman Goyal, Jingfei Du, Mandar Joshi, Danqi Chen, Omer Levy, Mike Lewis, Luke Zettlemoyer, and Veselin Stoyanov · 2019
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Pullnet: Open domain question answering with iterative retrieval on knowledge bases and text, 2019
Haitian Sun, Tania Bedrax-Weiss, and William W. Cohen · 2019
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Commonsenseqa: A question answering challenge targeting commonsense knowledge
Alon Talmor, Jonathan Herzig, Nicholas Lourie, and Jonathan Berant · 2019
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Language models are few-shot learners
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Language models are few-shot learners
Tom B. Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, Sandhini Agarwal, Ariel Herbert-Voss, Gretchen Krueger, Tom Henighan, Rewon Child, Aditya Ramesh, Daniel M. Ziegler, Jeffrey Wu, Clemens Winter, Christopher Hesse, Mark Chen, Eric Sigler, Mateusz Litwin, Scott Gray, Benjamin Chess, Jack Clark, Christopher Berner, Sam McCandlish, Alec Radford, Ilya Sutskever, and Dario Amodei · 2020
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Yunshi Lan and Jing Jiang · 2020
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Retrieval-augmented generation for knowledge-intensive nlp tasks, 2021
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 · 2021
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CREAK: A dataset for commonsense reasoning over entity knowledge
Yasumasa Onoe, Michael J. Q. Zhang, Eunsol Choi, and Greg Durrett · 2021
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Kilt: a benchmark for knowledge intensive language tasks, 2021
Fabio Petroni, Aleksandra Piktus, Angela Fan, Patrick Lewis, Majid Yazdani, Nicola De Cao, James Thorne, Yacine Jernite, Vladimir Karpukhin, Jean Maillard, Vassilis Plachouras, Tim Rocktäschel, and Sebastian Riedel · 2021
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Aakanksha Chowdhery, Sharan Narang, Jacob Devlin, Maarten Bosma, Gaurav Mishra, Adam Roberts, Paul Barham, Hyung Won Chung, Charles Sutton, Sebastian Gehrmann, Parker Schuh, Kensen Shi, Sasha Tsvyashchenko, Joshua Maynez, Abhishek Rao, Parker Barnes, Yi Tay, Noam Shazeer, Vinodkumar Prabhakaran, Emily Reif, Nan Du, Ben Hutchinson, Reiner Pope, James Bradbury, Jacob Austin, Michael Isard, Guy Gur-Ari, Pengcheng Yin, Toju Duke, Anselm Levskaya, Sanjay Ghemawat, Sunipa Dev, Henryk Michalewski, Xavier Garcia, Vedant Misra, Kevin Robinson, Liam Fedus, Denny Zhou, Daphne Ippolito, David Luan, Hyeontaek Lim, Barret Zoph, Alexander Spiridonov, Ryan Sepassi, David Dohan, Shivani Agrawal, Mark Omernick, Andrew M. Dai, Thanumalayan Sankaranarayana Pillai, Marie Pellat, Aitor Lewkowycz, Erica Moreira, Rewon Child, Oleksandr Polozov, Katherine Lee, Zongwei Zhou, Xuezhi Wang, Brennan Saeta, Mark Diaz, Orhan Firat, Michele Catasta, Jason Wei, Kathy Meier-Hellstern, Douglas Eck, Jeff Dean, Slav Petrov, and Noah Fiedel · 2022
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Gpt-4 technical report, 2023
OpenAI · 2023
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