416 citations · 1k across the 56 of their papers we have counts for
10 papers · 1 filter
From Good to Best: Two-Stage Training for Cross-lingual Machine Reading Comprehension
Nuo Chen, Linjun Shou, Min Gong +2
Cross-lingual Machine Reading Comprehension (xMRC) is challenging due to the lack of training data in low-resource languages. The recent approaches use training data only in a reso…
Learning from Multiple Noisy Augmented Data Sets for Better Cross-Lingual Spoken Language Understanding
Yingmei Guo, Linjun Shou, Jian Pei +4
Lack of training data presents a grand challenge to scaling out spoken language understanding (SLU) to low-resource languages. Although various data augmentation approaches have be…
A Joint and Domain-Adaptive Approach to Spoken Language Understanding
Linhao Zhang, Yu Shi, Linjun Shou +3
Spoken Language Understanding (SLU) is composed of two subtasks: intent detection (ID) and slot filling (SF). There are two lines of research on SLU. One jointly tackles these two…
Reinforced Iterative Knowledge Distillation for Cross-Lingual Named Entity Recognition
Shining Liang, Ming Gong, Jian Pei +4
Named entity recognition (NER) is a fundamental component in many applications, such as Web Search and Voice Assistants. Although deep neural networks greatly improve the performan…
CoSQA: 20,000+ Web Queries for Code Search and Question Answering
Junjie Huang, Duyu Tang, Linjun Shou +5
Finding codes given natural language query isb eneficial to the productivity of software developers. Future progress towards better semantic matching between query and code require…
Retrieval Enhanced Model for Commonsense Generation
Han Wang, Yang Liu, Chenguang Zhu +4
Commonsense generation is a challenging task of generating a plausible sentence describing an everyday scenario using provided concepts. Its requirement of reasoning over commonsen…
WhiteningBERT: An Easy Unsupervised Sentence Embedding Approach
Junjie Huang, Duyu Tang, Wanjun Zhong +5
Producing the embedding of a sentence in an unsupervised way is valuable to natural language matching and retrieval problems in practice. In this work, we conduct a thorough examin…
CodeXGLUE: A Machine Learning Benchmark Dataset for Code Understanding and Generation
Shuai Lu, Daya Guo, Shuo Ren +19
Benchmark datasets have a significant impact on accelerating research in programming language tasks. In this paper, we introduce CodeXGLUE, a benchmark dataset to foster machine le…
Generating Human Readable Transcript for Automatic Speech Recognition with Pre-trained Language Model
Junwei Liao, Yu Shi, Ming Gong +5
Modern Automatic Speech Recognition (ASR) systems can achieve high performance in terms of recognition accuracy. However, a perfectly accurate transcript still can be challenging t…
Improving Zero-shot Neural Machine Translation on Language-specific Encoders-Decoders
Junwei Liao, Yu Shi, Ming Gong +3
Recently, universal neural machine translation (NMT) with shared encoder-decoder gained good performance on zero-shot translation. Unlike universal NMT, jointly trained language-sp…