Trick Me If You Can: Human-in-the-loop Generation of Adversarial
Examples for Question Answering

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Trick Me If You Can: Human-in-the-loop Generation of Adversarial Examples for Question Answering

7 September 2018

Pedro Rodriguez

Jordan L. Boyd-Graber

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Papers citing "Trick Me If You Can: Human-in-the-loop Generation of Adversarial Examples for Question Answering"

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Title
TruthfulQA: Measuring How Models Mimic Human Falsehoods Stephanie C. Lin Jacob Hilton Owain Evans HILM 151 1,951 0 08 Sep 2021
QA Dataset Explosion: A Taxonomy of NLP Resources for Question Answering and Reading Comprehension Anna Rogers Matt Gardner Isabelle Augenstein 135 168 0 27 Jul 2021
Learning What Makes a Difference from Counterfactual Examples and Gradient Supervision Damien Teney Ehsan Abbasnejad Anton Van Den Hengel OOD SSL CML 93 119 0 20 Apr 2020
Adversarial NLI: A New Benchmark for Natural Language Understanding Yixin Nie Adina Williams Emily Dinan Joey Tianyi Zhou Jason Weston Douwe Kiela 183 1,013 0 31 Oct 2019
A Visual Analytics Framework for Adversarial Text Generation Brandon Laughlin C. Collins K. Sankaranarayanan K. El-Khatib AAML 37 10 0 24 Sep 2019
Detecting and Reducing Bias in a High Stakes Domain Ruiqi Zhong Yanda Chen D. Patton C. Selous Kathy McKeown 34 6 0 29 Aug 2019
Quizbowl: The Case for Incremental Question Answering Pedro Rodriguez Shi Feng Mohit Iyyer He He Jordan L. Boyd-Graber 67 50 0 09 Apr 2019
White-to-Black: Efficient Distillation of Black-Box Adversarial Attacks Yotam Gil Yoav Chai O. Gorodissky Jonathan Berant MLAU AAML 50 46 0 04 Apr 2019
Adversarial Attacks on Deep Learning Models in Natural Language Processing: A Survey W. Zhang Quan Z. Sheng A. Alhazmi Chenliang Li AAML 114 57 0 21 Jan 2019
What can AI do for me: Evaluating Machine Learning Interpretations in Cooperative Play Shi Feng Jordan L. Boyd-Graber HAI 82 130 0 23 Oct 2018
Interpreting Neural Networks With Nearest Neighbors Eric Wallace Shi Feng Jordan L. Boyd-Graber AAML FAtt MILM 140 54 0 08 Sep 2018