104 citations · 108 across the 2 of their papers we have counts for
6 papers
Unsupervised Parallel Corpus Mining on Web Data
Guokun Lai, Zihang Dai, Yiming Yang
With a large amount of parallel data, neural machine translation systems are able to deliver human-level performance for sentence-level translation. However, it is costly to label…
Funnel-Transformer: Filtering out Sequential Redundancy for Efficient Language Processing
Zihang Dai, Guokun Lai, Yiming Yang +1
With the success of language pretraining, it is highly desirable to develop more efficient architectures of good scalability that can exploit the abundant unlabeled data at a lower…
Correlation-aware Unsupervised Change-point Detection via Graph Neural Networks
Ruohong Zhang, Yu Hao, Donghan Yu +3
Change-point detection (CPD) aims to detect abrupt changes over time series data. Intuitively, effective CPD over multivariate time series should require explicit modeling of the d…
Bridging the domain gap in cross-lingual document classification
Guokun Lai, Barlas Oguz, Yiming Yang +1
The scarcity of labeled training data often prohibits the internationalization of NLP models to multiple languages. Recent developments in cross-lingual understanding (XLU) has mad…
Re-examination of the Role of Latent Variables in Sequence Modeling
Zihang Dai, Guokun Lai, Yiming Yang +1
With latent variables, stochastic recurrent models have achieved state-of-the-art performance in modeling sound-wave sequence. However, opposite results are also observed in other…
Stochastic WaveNet: A Generative Latent Variable Model for Sequential Data
Guokun Lai, Bohan Li, Guoqing Zheng +1
How to model distribution of sequential data, including but not limited to speech and human motions, is an important ongoing research problem. It has been demonstrated that model c…