Improving the interpretability of deep neural networks with stimulated learning. - Shawn Tan; Khe Chai Sim; Mark J. F. Gales (ASRU, 2015)

Solution of division by access to multiplication: Evidence from eye tracking. - Shawn Tan; Kasia Muldner; Jo-Anne LeFevre (CogSci, 2016)

Towards implicit complexity control using variable-depth deep neural networks for automatic speech recognition. - Shawn Tan; Khe Chai Sim (ICASSP, 2016)

Learning utterance-level normalisation using Variational Autoencoders for robust automatic speech recognition. - Shawn Tan; Khe Chai Sim (SLT, 2016)

Self-organized Hierarchical Softmax. - Yikang Shen; Shawn Tan; Christopher Joseph Pal; Aaron C. Courville (CoRR, 2017)

Improving Explorability in Variational Inference with Annealed Variational Objectives. - Chin-Wei Huang; Shawn Tan; Alexandre Lacoste; Aaron C. Courville (NeurIPS, 2018)

Generating Contradictory, Neutral, and Entailing Sentences. - Yikang Shen; Shawn Tan; Chin-Wei Huang; Aaron C. Courville (CoRR, 2018)

What strategies do adults use to solve fraction arithmetic problems? - Shawn Tan; Jo-Anne LeFevre (CogSci, 2019)

Ordered Neurons: Integrating Tree Structures into Recurrent Neural Networks. - Yikang Shen; Shawn Tan; Alessandro Sordoni; Aaron C. Courville (ICLR, 2019)

Ordered Memory. - Yikang Shen; Shawn Tan; Seyed Arian Hosseini; Zhouhan Lin; Alessandro Sordoni; Aaron C. Courville (NeurIPS, 2019)

Investigating Biases in Textual Entailment Datasets. - Shawn Tan; Yikang Shen; Chin-Wei Huang; Aaron C. Courville (CoRR, 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)

Scanpaths distinguish problem format in a math cognition task. - Samantha Stranc; Shawn Tan; Kasia Muldner (CogSci, 2020)

Recursive Top-Down Production for Sentence Generation with Latent Trees. - Shawn Tan; Yikang Shen; Alessandro Sordoni; Aaron C. Courville; Timothy J. O'Donnell (EMNLP (Findings), 2020)

Explicitly Modeling Syntax in Language Model improves Generalization. - Yikang Shen; Shawn Tan; Alessandro Sordoni; Siva Reddy; Aaron C. Courville (CoRR, 2020)

Explicitly Modeling Syntax in Language Models with Incremental Parsing and a Dynamic Oracle. - Yikang Shen; Shawn Tan; Alessandro Sordoni; Siva Reddy; Aaron C. Courville (NAACL-HLT, 2021)

Unsupervised Dependency Graph Network. - Yikang Shen; Shawn Tan; Alessandro Sordoni; Peng Li; Jie Zhou; Aaron C. Courville (ACL (1), 2022)

Learning to Dequantise with Truncated Flows. - Shawn Tan; Chin-Wei Huang; Alessandro Sordoni; Aaron C. Courville (ICLR, 2022)

Sparse Universal Transformer. - Shawn Tan; Yikang Shen; Zhenfang Chen; Aaron C. Courville; Chuang Gan 001 (EMNLP, 2023)

CattleDeSegNet: a joint approach to cattle denoising and interpretable segmentation. - Sivaji Retta; Ramarajulu Srinivasan; Shawn Tan (ICMV, 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 036 (VCIP, 2023)

ModuleFormer: Learning Modular Large Language Models From Uncurated Data. - Yikang Shen; Zheyu Zhang; Tianyou Cao; Shawn Tan; Zhenfang Chen; Chuang Gan 001 (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 (CoRR, 2023)

MTYOLO: A Multi-Task Model to Concurrently Obtain the Vital Characteristics of Individuals or Animals. - Kian Eng Ong; Sivaji Retta; Ramarajulu Srinivasan; Shawn Tan; Jun Liu (ICME Workshops, 2024)

Scattered Mixture-of-Experts Implementation. - Shawn Tan; Yikang Shen; Rameswar Panda; Aaron C. Courville (CoRR, 2024)

Power Scheduler: A Batch Size and Token Number Agnostic Learning Rate Scheduler. - Yikang Shen; Matthew Stallone; Mayank Mishra; Gaoyuan Zhang; Shawn Tan; Aditya Prasad; Adriana Meza Soria; David D. Cox; Rameswar Panda (CoRR, 2024)

Stick-breaking Attention. - Shawn Tan; Yikang Shen; Songlin Yang; Aaron C. Courville; Rameswar Panda (CoRR, 2024)

Scaling Stick-Breaking Attention: An Efficient Implementation and In-depth Study. - Shawn Tan; Songlin Yang; Aaron C. Courville; Rameswar Panda; Yikang Shen (ICLR, 2025)

Do Larger Language Models Imply Better Reasoning? A Pretraining Scaling Law for Reasoning. - Xinyi Wang 003; Shawn Tan; Mingyu Jin; William Yang Wang; Rameswar Panda; Yikang Shen (CoRR, 2025)

PaTH Attention: Position Encoding via Accumulating Householder Transformations. - Songlin Yang; Yikang Shen; Kaiyue Wen; Shawn Tan; Mayank Mishra; Liliang Ren; Rameswar Panda; Yoon Kim (CoRR, 2025)