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Question answering over knowledge bases is considered a difficult problem due to the challenge of generalizing to a wide variety of possible natural language questions.
Pullnet: Open domain question answering with iterative retrieval on knowledge bases and text
Haitian Sun, Tania Bedrax-Weiss, and William W. Cohen. 2019 · 1904
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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, T. J. Henighan, Rewon Child, Aditya Ramesh, Daniel M. Ziegler, Jeff 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 · 2005
Earlier work this paper cites.
Freebase: a collaboratively created graph database for structuring human knowledge
Kurt D. Bollacker, Colin Evans, Praveen K. Paritosh, Tim Sturge, and Jamie Taylor. 2008 · 2008
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Few-shot complex knowledge base question answering via meta reinforcement learning
Yuncheng Hua, Yuan-Fang Li, Gholamreza Haffari, Guilin Qi, and Tongtong Wu. 2020 · 2010
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Semantic parsing on freebase from question-answer pairs
Jonathan Berant, Andrew Chou, Roy Frostig, and Percy Liang. 2013 · 2013
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Semantic parsing via staged query graph generation: Question answering with knowledge base
Scott Wen-tau Yih, Ming-Wei Chang, Xiaodong He, and Jianfeng Gao. 2015 · 2015
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Language to logical form with neural attention
Li Dong and Mirella Lapata. 2016 · 2016
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Key-value memory networks for directly reading documents
Alexander H. Miller, Adam Fisch, Jesse Dodge, Amir-Hossein Karimi, Antoine Bordes, and Jason Weston. 2016 · 2016
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On generating characteristic-rich question sets for qa evaluation
Yu Su, Huan Sun, Brian M. Sadler, Mudhakar Srivatsa, Izzeddin Gur, Zenghui Yan, and Xifeng Yan. 2016 · 2016
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The value of semantic parse labeling for knowledge base question answering
Wen-tau Yih, Matthew Richardson, Christopher Meek, Ming-Wei Chang, and Jina Suh. 2016 · 2016
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Universal semantic parsing
Siva Reddy, Oscar Täckström, Slav Petrov, Mark Steedman, and Mirella Lapata. 2017 · 2017
Earlier work this paper cites.
Variational reasoning for question answering with knowledge graph
Yuyu Zhang, Hanjun Dai, Zornitsa Kozareva, Alex Smola, and Le Song. 2017 · 2017
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Open domain question answering using early fusion of knowledge bases and text
Haitian Sun, Bhuwan Dhingra, Manzil Zaheer, Kathryn Mazaitis, Ruslan Salakhutdinov, and William W. Cohen. 2018 · 2018
Earlier work this paper cites.
The web as a knowledge-base for answering complex questions
Alon Talmor and Jonathan Berant. 2018 · 2018
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A survey of question answering over knowledge base
Peiyun Wu, Xiaowang Zhang, and Zhiyong Feng. 2019 · 2019
Cited alongside, same era.
Query graph generation for answering multi-hop complex questions from knowledge bases
Yunshi Lan and Jing Jiang. 2020 · 2020
Cited alongside, same era.
Improving multi-hop question answering over knowledge graphs using knowledge base embeddings
Apoorv Saxena, Aditay Tripathi, and Partha Pratim Talukdar. 2020 · 2020
Cited alongside, same era.
Sparqa: Skeleton-based semantic parsing for complex questions over knowledge bases
Yawei Sun, Lingling Zhang, Gong Cheng, and Yuzhong Qu. 2020 · 2020
Cited alongside, same era.
Beyond i.i.d.: Three levels of generalization for question answering on knowledge bases
Yu Gu, Sue E. Kase, Michelle T. Vanni, Brian M. Sadler, Percy Liang, Xifeng Yan, and Yu Su. 2020 · 2021
Cited alongside, same era.
Structured information extraction from complex scientific text with fine-tuned large language models
Alexander Dunn, John Dagdelen, Nicholas Walker, Sanghoon Lee, Andrew S. Rosen, Gerbrand Ceder, Kristin Persson, and Anubhav Jain. 2022 · 2022
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Pal: Program-aided language models
Luyu Gao, Aman Madaan, Shuyan Zhou, Uri Alon, Pengfei Liu, Yiming Yang, Jamie Callan, and Graham Neubig. 2022 · 2022
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Knowledge base question answering: A semantic parsing perspective
Yu Gu, Vardaan Pahuja, Gong Cheng, and Yu Su. 2022 · 2022
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Arcaneqa: Dynamic program induction and contextualized encoding for knowledge base question answering
Yu Gu and Yu Su. 2022 · 2022
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Gaole He, Yunshi Lan, Jing Jiang, Wayne Xin Zhao, and Ji rong Wen. 2021 · 2021
Cited alongside, same era.
Unsupervised dense information retrieval with contrastive learning
Gautier Izacard, Mathilde Caron, Lucas Hosseini, Sebastian Riedel, Piotr Bojanowski, Armand Joulin, and Edouard Grave. 2021 · 2021
Cited alongside, same era.
A survey on complex knowledge base question answering: Methods, challenges and solutions
Yunshi Lan, Gaole He, Jinhao Jiang, Jing Jiang, Wayne Xin Zhao, and Ji rong Wen. 2021 · 2021
Cited alongside, same era.
What makes good in-context examples for gpt-3?
Jiachang Liu, Dinghan Shen, Yizhe Zhang, Bill Dolan, Lawrence Carin, and Weizhu Chen. 2021 · 2021
Cited alongside, same era.
Show your work: Scratchpads for intermediate computation with language models
Maxwell Nye, Anders Johan Andreassen, Guy Gur-Ari, Henryk Michalewski, Jacob Austin, David Bieber, David Dohan, Aitor Lewkowycz, Maarten Bosma, David Luan, Charles Sutton, and Augustus Odena. 2021 · 2021
Cited alongside, same era.
An explanation of in-context learning as implicit bayesian inference
Sang Michael Xie, Aditi Raghunathan, Percy Liang, and Tengyu Ma. 2021 · 2021
Cited alongside, same era.
Rng-kbqa: Generation augmented iterative ranking for knowledge base question answering
Xi Ye, Semih Yavuz, Kazuma Hashimoto, Yingbo Zhou, and Caiming Xiong. 2021 · 2021
Cited alongside, same era.
Takeshi Kojima, Shixiang Shane Gu, Machel Reid, Yutaka Matsuo, and Yusuke Iwasawa. 2022 · 2022
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Can language models learn from explanations in context?
Andrew K. Lampinen, Ishita Dasgupta, Stephanie C. Y. Chan, Kory Matthewson, Michael Henry Tessler, Antonia Creswell, James L. McClelland, Jane X. Wang, and Felix Hill. 2022 · 2022
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Solving quantitative reasoning problems with language models
Aitor Lewkowycz, Anders Andreassen, David Dohan, Ethan Dyer, Henryk Michalewski, Vinay Ramasesh, Ambrose Slone, Cem Anil, Imanol Schlag, Theo Gutman-Solo, Yuhuai Wu, Behnam Neyshabur, Guy Gur-Ari, and Vedant Misra. 2022 · 2022
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Rethinking the role of demonstrations: What makes in-context learning work?
Sewon Min, Xinxi Lyu, Ari Holtzman, Mikel Artetxe, Mike Lewis, Hannaneh Hajishirzi, and Luke Zettlemoyer. 2022 · 2022
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In-context learning and induction heads
Catherine Olsson, Nelson Elhage, Neel Nanda, Nicholas Joseph, Nova DasSarma, Tom Henighan, Ben Mann, Amanda Askell, Yuntao Bai, Anna Chen, Tom Conerly, Dawn Drain, Deep Ganguli, Zac Hatfield-Dodds, Danny Hernandez, Scott Johnston, Andy Jones, Jackson Kernion, Liane Lovitt, Kamal Ndousse, Dario Amodei, Tom Brown, Jack Clark, Jared Kaplan, Sam McCandlish, and Chris Olah. 2022 · 2022
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Tiara: Multi-grained retrieval for robust question answering over large knowledge bases
Yiheng Shu, Zhiwei Yu, Yuhan Li, Börje F. Karlsson, Tingting Ma, Yuzhong Qu, and Chin-Yew Lin. 2022 · 2022
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Challenging big-bench tasks and whether chain-of-thought can solve them
Mirac Suzgun, Nathan Scales, Nathanael Scharli, Sebastian Gehrmann, Yi Tay, Hyung Won Chung, Aakanksha Chowdhery, Quoc V. Le, Ed Huai hsin Chi, Denny Zhou, and Jason Wei. 2022 · 2022
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Decaf: Joint decoding of answers and logical forms for question answering over knowledge bases
Donghan Yu, Shenmin Zhang, Patrick Ng, Henghui Zhu, Alexander Hanbo Li, J. Wang, Yiqun Hu, William Wang, Zhiguo Wang, and Bing Xiang. 2022 · 2022
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S2ql: Retrieval augmented zero-shot question answering over knowledge graph
Daoguang Zan, Sirui Wang, Hongzhi Zhang, Yuanmeng Yan, Wei Wu, Bei Guan, and Yongji Wang. 2022 · 2022
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