64 citations · 285 across the 10 of their papers we have counts for
11 papers · 1 filter
Lightweight and Efficient Neural Natural Language Processing with Quaternion Networks
Yi Tay, Aston Zhang, Luu Anh Tuan +5
Many state-of-the-art neural models for NLP are heavily parameterized and thus memory inefficient. This paper proposes a series of lightweight and memory efficient neural architect…
Simple and Effective Curriculum Pointer-Generator Networks for Reading Comprehension over Long Narratives
Yi Tay, Shuohang Wang, Luu Anh Tuan +6
This paper tackles the problem of reading comprehension over long narratives where documents easily span over thousands of tokens. We propose a curriculum learning (CL) based Point…
Recurrently Controlled Recurrent Networks
Yi Tay, Luu Anh Tuan, Siu Cheung Hui
Recurrent neural networks (RNNs) such as long short-term memory and gated recurrent units are pivotal building blocks across a broad spectrum of sequence modeling problems. This pa…
Densely Connected Attention Propagation for Reading Comprehension
Yi Tay, Luu Anh Tuan, Siu Cheung Hui +1
We propose DecaProp (Densely Connected Attention Propagation), a new densely connected neural architecture for reading comprehension (RC). There are two distinct characteristics of…
Co-Stack Residual Affinity Networks with Multi-level Attention Refinement for Matching Text Sequences
Yi Tay, Luu Anh Tuan, Siu Cheung Hui
Learning a matching function between two text sequences is a long standing problem in NLP research. This task enables many potential applications such as question answering and par…
Multi-Cast Attention Networks for Retrieval-based Question Answering and Response Prediction
Yi Tay, Luu Anh Tuan, Siu Cheung Hui
Attention is typically used to select informative sub-phrases that are used for prediction. This paper investigates the novel use of attention as a form of feature augmentation, i.…