82 citations · 140 across the 9 of their papers we have counts for
13 papers
CoRAL: a Context-aware Croatian Abusive Language Dataset
Ravi Shekhar, Mladen Karan, Matthew Purver
In light of unprecedented increases in the popularity of the internet and social media, comment moderation has never been a more relevant task. Semi-automated comment moderation sy…
Measuring and Improving Compositional Generalization in Text-to-SQL via Component Alignment
Yujian Gan, Xinyun Chen, Qiuping Huang +1
In text-to-SQL tasks -- as in much of NLP -- compositional generalization is a major challenge: neural networks struggle with compositional generalization where training and test d…
Not All Comments are Equal: Insights into Comment Moderation from a Topic-Aware Model
Elaine Zosa, Ravi Shekhar, Mladen Karan +1
Moderation of reader comments is a significant problem for online news platforms. Here, we experiment with models for automatic moderation, using a dataset of comments from a popul…
Exploring Underexplored Limitations of Cross-Domain Text-to-SQL Generalization
Yujian Gan, Xinyun Chen, Matthew Purver
Recently, there has been significant progress in studying neural networks for translating text descriptions into SQL queries under the zero-shot cross-domain setting. Despite achie…
Natural SQL: Making SQL Easier to Infer from Natural Language Specifications
Yujian Gan, Xinyun Chen, Jinxia Xie +4
Addressing the mismatch between natural language descriptions and the corresponding SQL queries is a key challenge for text-to-SQL translation. To bridge this gap, we propose an SQ…
Evaluation of contextual embeddings on less-resourced languages
Matej Ulčar, Aleš Žagar, Carlos S. Armendariz +4
The current dominance of deep neural networks in natural language processing is based on contextual embeddings such as ELMo, BERT, and BERT derivatives. Most existing work focuses…