109 citations · 284 across the 11 of their papers we have counts for
11 papers
A Self-enhancement Approach for Domain-specific Chatbot Training via Knowledge Mining and Digest
Ruohong Zhang, Luyu Gao, Chen Zheng +6
Large Language Models (LLMs), despite their great power in language generation, often encounter challenges when dealing with intricate and knowledge-demanding queries in specific d…
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…
Large-scale Cloze Test Dataset Created by Teachers
Qizhe Xie, Guokun Lai, Zihang Dai +1
Cloze tests are widely adopted in language exams to evaluate students' language proficiency. In this paper, we propose the first large-scale human-created cloze test dataset CLOTH,…
Learning Depthwise Separable Graph Convolution from Data Manifold
Guokun Lai, Hanxiao Liu, Yiming Yang
Convolution Neural Network (CNN) has gained tremendous success in computer vision tasks with its outstanding ability to capture the local latent features. Recently, there has been…
RACE: Large-scale ReAding Comprehension Dataset From Examinations
Guokun Lai, Qizhe Xie, Hanxiao Liu +2
We present RACE, a new dataset for benchmark evaluation of methods in the reading comprehension task. Collected from the English exams for middle and high school Chinese students i…
Modeling Long- and Short-Term Temporal Patterns with Deep Neural Networks
Guokun Lai, Wei-Cheng Chang, Yiming Yang +1
Multivariate time series forecasting is an important machine learning problem across many domains, including predictions of solar plant energy output, electricity consumption, and…