5 citations · 17 across the 6 of their papers we have counts for
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Capturing Greater Context for Question Generation
Luu Anh Tuan, Darsh J Shah, Regina Barzilay
Automatic question generation can benefit many applications ranging from dialogue systems to reading comprehension. While questions are often asked with respect to long documents,…
Automatic Fact-guided Sentence Modification
Darsh J Shah, Tal Schuster, Regina Barzilay
Online encyclopediae like Wikipedia contain large amounts of text that need frequent corrections and updates. The new information may contradict existing content in encyclopediae.…
Towards Debiasing Fact Verification Models
Tal Schuster, Darsh J Shah, Yun Jie Serene Yeo +3
Fact verification requires validating a claim in the context of evidence. We show, however, that in the popular FEVER dataset this might not necessarily be the case. Claim-only cla…
The Limitations of Stylometry for Detecting Machine-Generated Fake News
Tal Schuster, Roei Schuster, Darsh J Shah +1
Recent developments in neural language models (LMs) have raised concerns about their potential misuse for automatically spreading misinformation. In light of these concerns, severa…
Robust Zero-Shot Cross-Domain Slot Filling with Example Values
Darsh J Shah, Raghav Gupta, Amir A Fayazi +1
Task-oriented dialog systems increasingly rely on deep learning-based slot filling models, usually needing extensive labeled training data for target domains. Often, however, littl…