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Paper co-authored with the University of Maryland team accepted at TACL

2019-09-02

A paper co-authored by Yamada and the University of Maryland team was accepted at Transactions of the Association for Computational Linguistics (TACL), a leading journal in computational linguistics and natural language processing.

In this paper, a new method for developing question answering datasets that are difficult for current state-of-the-art AI to solve is proposed.

Abou the paper

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

Eric Wallace (U. Maryland), Pedro Rodriguez (U. Maryland), Shi Feng (U. Maryland), Ikuya Yamada, Jordan Boyd-Graber (U. Maryland) Transactions of the Association for Computational Linguistics (TACL), 2019

Access to paper: https://www.transacl.org/ojs/index.php/tacl/article/view/1711