Search
Now showing items 1-10 of 15
Temporal Mental Health Dynamics on Social Media
(ACL, 2020)
We describe a set of experiments for building a temporal mental health dynamics system. We utilise a pre-existing methodology for distant-supervision of mental health data mining from social media platforms and deploy the ...
Evaluation of contextual embeddings on less-resourced languages
(2021)
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 on English; in contrast, we present here ...
Not All Comments are Equal: Insights into Comment Moderation from a Topic-Aware Model
(2021)
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 popular Croatian newspaper. Our analysis shows ...
A Longitudinal Multi-modal Dataset for Dementia Monitoring and Diagnosis
(2021)
Dementia is a family of neurogenerative conditions affecting memory and cognition in an increasing number of individuals in our globally aging population. Automated analysis of language, speech and paralinguistic indicators ...
Exploring Underexplored Limitations of Cross-Domain Text-to-SQL Generalization
(2021)
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 achieving good performance on some public ...
Towards Robustness of Text-to-SQL Models against Synonym Substitution
(2021)
Recently, there has been significant progress in studying neural networks to translate text descriptions into SQL queries. Despite achieving good performance on some public benchmarks, existing text-to-SQL models typically ...
Natural SQL: Making SQL Easier to Infer from Natural Language Specifications
(2021)
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 SQL intermediate representation (IR) called ...
Measuring and Improving Compositional Generalization in Text-to-SQL via Component Alignment
(2022-05-04)
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 distributions differ. However, most recent ...