activity
20192022
most citedCodeXGLUE: A Machine Learning Benchmark Dataset for Code Understanding and Generation

416 citations · 566 across the 28 of their papers we have counts for

collaborators

32 papers

cs.CL2021

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…

cs.CL20211 cited

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…

cs.CL20215 cited

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…

cs.CL20212 cited

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…

cs.CL2021

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…

cs.CL2021

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…