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Found 10 papers, 3 papers with code
Language as a Latent Sequence: deep latent variable models for semi-supervised paraphrase generation
To leverage information from text pairs, we additionally introduce a novel supervised model we call dual directional learning (DDL), which is designed to integrate with our proposed VSAR model.
Religion and Spirituality on Social Media in the Aftermath of the Global Pandemic
During the COVID-19 pandemic, the Church closed its physical doors for the first time in about 800 years, which is, arguably, a cataclysmic event.
Incorporating Emotions into Health Mention Classification Task on Social Media
The health mention classification (HMC) task is the process of identifying and classifying mentions of health-related concepts in text.
Multi-task Learning for Personal Health Mention Detection on Social Media
Detecting personal health mentions on social media is essential to complement existing health surveillance systems.
INTERACTION: A Generative XAI Framework for Natural Language Inference Explanations
XAI with natural language processing aims to produce human-readable explanations as evidence for AI decision-making, which addresses explainability and transparency.
Decision Making
Explainable Artificial Intelligence (XAI)
+2
Exploring Bayesian Deep Learning for Urgent Instructor Intervention Need in MOOC Forums
Learners may post their feelings of confusion and struggle in the respective MOOC forums, but with the large volume of posts and high workloads for MOOC instructors, it is unlikely that the instructors can identify all learners requiring intervention.
Revealing the Hidden Patterns: A Comparative Study on Profiling Subpopulations of MOOC Students
Massive Open Online Courses (MOOCs) exhibit a remarkable heterogeneity of students.
Predicting MOOCs Dropout Using Only Two Easily Obtainable Features from the First Week's Activities
While Massive Open Online Course (MOOCs) platforms provide knowledge in a new and unique way, the very high number of dropouts is a significant drawback.
Nowcasting the Stance of Social Media Users in a Sudden Vote: The Case of the Greek Referendum
Modelling user voting intention in social media is an important research area, with applications in analysing electorate behaviour, online political campaigning and advertising.
Can We Assess Mental Health through Social Media and Smart Devices? Addressing Bias in Methodology and Evaluation
Predicting mental health from smartphone and social media data on a longitudinal basis has recently attracted great interest, with very promising results being reported across many studies.
