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The Natural Language for Optimization (NL4Opt) Competition was created to investigate methods of extracting the meaning and formulation of an optimization problem based on its text description.
Mike Lewis, Yinhan Liu, Naman Goyal, Marjan Ghazvininejad, Abdelrahman Mohamed, Omer Levy, Ves Stoyanov, and Luke Zettlemoyer · 1910
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Colin Raffel, Noam Shazeer, Adam Roberts, Katherine Lee, Sharan Narang, Michael Matena, Yanqi Zhou, Wei Li, and Peter J. Liu · 1910
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Alexis Conneau, Kartikay Khandelwal, Naman Goyal, Vishrav Chaudhary, Guillaume Wenzek, Francisco Guzmán, Edouard Grave, Myle Ott, Luke Zettlemoyer, and Veselin Stoyanov · 1911
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A new polynomial-time algorithm for linear programming
N. Karmarkar · 1984
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Supply chain partnerships: opportunities for operations research
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The (dantzig) simplex method for linear programming
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Production planning by mixed integer programming , volume 149
Yves Pochet and Laurence A Wolsey · 2006
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Model building in mathematical programming
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Language to logical form with neural attention
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Victor Zhong, Caiming Xiong, and Richard Socher · 2017
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Identifying locations for new bike-sharing stations in glasgow: an analysis of spatial equity and demand factors
Jeneva Beairsto, Yufan Tian, Linyu Zheng, Qunshan Zhao, and Jinhyun Hong · 2021
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SemEval-2021 task 8: MeasEval – extracting counts and measurements and their related contexts
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Pengcheng He, Jianfeng Gao, and Weizhu Chen · 2021
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Are NLP models really able to solve simple math word problems?
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