5 citations · 17 across the 6 of their papers we have counts for
11 papers
Reducing Target Group Bias in Hate Speech Detectors
Darsh J Shah, Sinong Wang, Han Fang +2
The ubiquity of offensive and hateful content on online fora necessitates the need for automatic solutions that detect such content competently across target groups. In this paper…
Generating Related Work
Darsh J Shah, Regina Barzilay
Communicating new research ideas involves highlighting similarities and differences with past work. Authors write fluent, often long sections to survey the distinction of a new pap…
Nutribullets Hybrid: Multi-document Health Summarization
Darsh J Shah, Lili Yu, Tao Lei +1
We present a method for generating comparative summaries that highlights similarities and contradictions in input documents. The key challenge in creating such summaries is the lac…
Nutri-bullets: Summarizing Health Studies by Composing Segments
Darsh J Shah, Lili Yu, Tao Lei +1
We introduce \emph{Nutri-bullets}, a multi-document summarization task for health and nutrition. First, we present two datasets of food and health summaries from multiple scientifi…
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…
Multi-Source Domain Adaptation with Mixture of Experts
Jiang Guo, Darsh J Shah, Regina Barzilay
We propose a mixture-of-experts approach for unsupervised domain adaptation from multiple sources. The key idea is to explicitly capture the relationship between a target example a…
Adversarial Domain Adaptation for Duplicate Question Detection
Darsh J Shah, Tao Lei, Alessandro Moschitti +2
We address the problem of detecting duplicate questions in forums, which is an important step towards automating the process of answering new questions. As finding and annotating s…