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Sentiment Interpretable Logic Tensor Network for Aspect-Term Sentiment Analysis
SILTN is interpretable because it is a neurosymbolic formalism and a computational model that supports learning and reasoning about data with a differentiable first-order logic language (FOL).
More is Better: Deep Domain Adaptation with Multiple Sources
Domain adaptation (DA) aims to address this problem by aligning the distributions between the source and target domains.
A Logically Consistent Chain-of-Thought Approach for Stance Detection
Zero-shot stance detection (ZSSD) aims to detect stances toward unseen targets.
Investigating Chain-of-thought with ChatGPT for Stance Detection on Social Media
Stance detection predicts attitudes towards targets in texts and has gained attention with the rise of social media.
Blending Knowledge in Deep Recurrent Networks for Adverse Event Prediction at Hospital Discharge
Deep learning architectures have an extremely high-capacity for modeling complex data in a wide variety of domains.
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