Shawn Tan

According to our database, Shawn Tan authored at least 22 papers between 2015 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Scattered Mixture-of-Experts Implementation.

Shawn Tan, Yikang Shen, Rameswar Panda, Aaron C. Courville

CoRR, 2024

2023

ModuleFormer: Learning Modular Large Language Models From Uncurated Data.

Yikang Shen, Zheyu Zhang, Tianyou Cao, Shawn Tan, Zhenfang Chen, Chuang Gan

CoRR, 2023

CattleEyeView: A Multi-task Top-down View Cattle Dataset for Smarter Precision Livestock Farming.

Kian Eng Ong, Sivaji Retta, Ramarajulu Srinivasan, Shawn Tan, Jun Liu

Proceedings of the IEEE International Conference on Visual Communications and Image Processing, 2023

Sparse Universal Transformer.

Shawn Tan, Yikang Shen, Zhenfang Chen, Aaron C. Courville, Chuang Gan

Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

2022

Learning to Dequantise with Truncated Flows.

Shawn Tan, Chin-Wei Huang, Alessandro Sordoni, Aaron C. Courville

Proceedings of the Tenth International Conference on Learning Representations, 2022

Unsupervised Dependency Graph Network.

Yikang Shen, Shawn Tan, Alessandro Sordoni, Peng Li, Jie Zhou, Aaron C. Courville

Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2022

2021

Explicitly Modeling Syntax in Language Models with Incremental Parsing and a Dynamic Oracle.

Yikang Shen, Shawn Tan, Alessandro Sordoni, Siva Reddy, Aaron C. Courville

Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2021

2020

Explicitly Modeling Syntax in Language Model improves Generalization.

Yikang Shen, Shawn Tan, Alessandro Sordoni, Siva Reddy, Aaron C. Courville

CoRR, 2020

Recursive Top-Down Production for Sentence Generation with Latent Trees.

Shawn Tan, Yikang Shen, Alessandro Sordoni, Aaron C. Courville, Timothy J. O'Donnell

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2020, 2020

Scanpaths distinguish problem format in a math cognition task.

Samantha Stranc, Shawn Tan, Kasia Muldner

Proceedings of the 42th Annual Meeting of the Cognitive Science Society, 2020

2019

Icentia11K: An Unsupervised Representation Learning Dataset for Arrhythmia Subtype Discovery.

Shawn Tan, Guillaume Androz, Ahmad Chamseddine, Pierre Fecteau, Aaron C. Courville, Yoshua Bengio, Joseph Paul Cohen

CoRR, 2019

Investigating Biases in Textual Entailment Datasets.

Shawn Tan, Yikang Shen, Chin-Wei Huang, Aaron C. Courville

CoRR, 2019

Ordered Memory.

Yikang Shen, Shawn Tan, Seyed Arian Hosseini, Zhouhan Lin, Alessandro Sordoni, Aaron C. Courville

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Ordered Neurons: Integrating Tree Structures into Recurrent Neural Networks.

Yikang Shen, Shawn Tan, Alessandro Sordoni, Aaron C. Courville

Proceedings of the 7th International Conference on Learning Representations, 2019

What strategies do adults use to solve fraction arithmetic problems?

Shawn Tan, Jo-Anne LeFevre

Proceedings of the 41th Annual Meeting of the Cognitive Science Society, 2019

2018

Generating Contradictory, Neutral, and Entailing Sentences.

Yikang Shen, Shawn Tan, Chin-Wei Huang, Aaron C. Courville

CoRR, 2018

Improving Explorability in Variational Inference with Annealed Variational Objectives.

Chin-Wei Huang, Shawn Tan, Alexandre Lacoste, Aaron C. Courville

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

2017

Self-organized Hierarchical Softmax.

Yikang Shen, Shawn Tan, Christopher Joseph Pal, Aaron C. Courville

CoRR, 2017

2016

Learning utterance-level normalisation using Variational Autoencoders for robust automatic speech recognition.

Shawn Tan, Khe Chai Sim

Proceedings of the 2016 IEEE Spoken Language Technology Workshop, 2016

Towards implicit complexity control using variable-depth deep neural networks for automatic speech recognition.

Shawn Tan, Khe Chai Sim

Proceedings of the 2016 IEEE International Conference on Acoustics, 2016

Solution of division by access to multiplication: Evidence from eye tracking.

Shawn Tan, Kasia Muldner, Jo-Anne LeFevre

Proceedings of the 38th Annual Meeting of the Cognitive Science Society, 2016

2015

Improving the interpretability of deep neural networks with stimulated learning.

Shawn Tan, Khe Chai Sim, Mark J. F. Gales

Proceedings of the 2015 IEEE Workshop on Automatic Speech Recognition and Understanding, 2015