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User-supplied reviews are widely and increasingly used to enhance e- commerce and other websites. Because reviews can be numerous and varying in quality, it is important to assess how helpful …...
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Sentiment classification aims to automati- cally predict sentiment polarity (e.g., pos- itive or negative) of user generated sen- timent data (e.g., reviews, blogs). Due to the mismatch among different domains, …...
Extracting Aspect Specific Opinion Expressions
Opinionated expression extraction is a cen- tral problem in fine-grained sentiment anal- ysis. Most existing works focus on either generic subjective expression or aspect ex- pression extraction. However, in opinion …...
SSMBA: Self-Supervised Manifold Based Data Augmentation for Improving Out-of-Domain Robustness
AbstractModels that perform well on a training domain often fail to generalize to out-of-domain (OOD) examples. Data augmentation is a common method used to prevent overfitting and improve OOD generalization. …...
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AbstractLanguage agnostic and semantic-language information isolation is an emerging research direction for multilingual representations models. We explore this problem from a novel angle of geometric algebra and semantic space. A …...
Adversarial Learning of Poisson Factorisation Model for Gauging Brand Sentiment in User Reviews
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Learning Universal Authorship Representations
AbstractDetermining whether two documents were composed by the same author, also known as authorship verification, has traditionally been tackled using statistical methods. Recently, authorship representations learned using neural networks have …...
Detecting Label Errors by Using Pre-Trained Language Models
AbstractWe show that large pre-trained language models are inherently highly capable of identifying label errors in natural language datasets: simply examining out-of-sample data points in descending order of fine-tuned task …...