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Generate-and-Retrieve: use your predictions to improve retrieval for semantic parsing


Sep 29, 2022
Yury Zemlyanskiy, Michiel de Jong, Joshua Ainslie, Panupong Pasupat, Peter Shaw, Linlu Qiu, Sumit Sanghai, Fei Sha

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* To appear in the proceedings of COLING 2022 

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ALMA: Hierarchical Learning for Composite Multi-Agent Tasks


May 27, 2022
Shariq Iqbal, Robby Costales, Fei Sha

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Evaluating the Impact of Model Scale for Compositional Generalization in Semantic Parsing


May 24, 2022
Linlu Qiu, Peter Shaw, Panupong Pasupat, Tianze Shi, Jonathan Herzig, Emily Pitler, Fei Sha, Kristina Toutanova

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Possibility Before Utility: Learning And Using Hierarchical Affordances


Mar 23, 2022
Robby Costales, Shariq Iqbal, Fei Sha

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* ICLR 2022 camera-ready 

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Policy Learning and Evaluation with Randomized Quasi-Monte Carlo


Feb 21, 2022
Sebastien M. R. Arnold, Pierre L'Ecuyer, Liyu Chen, Yi-fan Chen, Fei Sha

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* AISTATS 2022 camera ready; more info at: http://seba1511.net/projects/qrl/ 

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Improving Compositional Generalization with Latent Structure and Data Augmentation


Dec 14, 2021
Linlu Qiu, Peter Shaw, Panupong Pasupat, Paweł Krzysztof Nowak, Tal Linzen, Fei Sha, Kristina Toutanova

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Co-training Transformer with Videos and Images Improves Action Recognition


Dec 14, 2021
Bowen Zhang, Jiahui Yu, Christopher Fifty, Wei Han, Andrew M. Dai, Ruoming Pang, Fei Sha

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Learning to Generalize Compositionally by Transferring Across Semantic Parsing Tasks


Nov 09, 2021
Wang Zhu, Peter Shaw, Tal Linzen, Fei Sha

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HyperPINN: Learning parameterized differential equations with physics-informed hypernetworks


Oct 28, 2021
Filipe de Avila Belbute-Peres, Yi-fan Chen, Fei Sha

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