12 citations · 29 across the 52 of their papers we have counts for
6 papers · 1 filter
Learning to Infer from Unlabeled Data: A Semi-supervised Learning Approach for Robust Natural Language Inference
Mobashir Sadat, Cornelia Caragea
Natural Language Inference (NLI) or Recognizing Textual Entailment (RTE) aims at predicting the relation between a pair of sentences (premise and hypothesis) as entailment, contrad…
Why Do You Feel This Way? Summarizing Triggers of Emotions in Social Media Posts
Hongli Zhan, Tiberiu Sosea, Cornelia Caragea +1
Crises such as the COVID-19 pandemic continuously threaten our world and emotionally affect billions of people worldwide in distinct ways. Understanding the triggers leading to peo…
A Data Cartography based MixUp for Pre-trained Language Models
Seo Yeon Park, Cornelia Caragea
MixUp is a data augmentation strategy where additional samples are generated during training by combining random pairs of training samples and their labels. However, selecting rand…
SciNLI: A Corpus for Natural Language Inference on Scientific Text
Mobashir Sadat, Cornelia Caragea
Existing Natural Language Inference (NLI) datasets, while being instrumental in the advancement of Natural Language Understanding (NLU) research, are not related to scientific text…
On the Calibration of Pre-trained Language Models using Mixup Guided by Area Under the Margin and Saliency
Seo Yeon Park, Cornelia Caragea
A well-calibrated neural model produces confidence (probability outputs) closely approximated by the expected accuracy. While prior studies have shown that mixup training as a data…
On the Evaluation of Answer-Agnostic Paragraph-level Multi-Question Generation
Jishnu Ray Chowdhury, Debanjan Mahata, Cornelia Caragea
We study the task of predicting a set of salient questions from a given paragraph without any prior knowledge of the precise answer. We make two main contributions. First, we propo…