Empirical Error Modeling Improves Robustness of Noisy Neural Sequence Labeling

25 May 2021

Papers citing "Empirical Error Modeling Improves Robustness of Noisy Neural Sequence Labeling"

5 / 5 papers shown

Title
NL-Augmenter: A Framework for Task-Sensitive Natural Language Augmentation Kaustubh D. Dhole Varun Gangal Sebastian Gehrmann Aadesh Gupta Zhenhao Li ... Tianbao Xie Usama Yaseen Michael A. Yee Jing Zhang Yue Zhang 174 86 0 06 Dec 2021
Robust Encodings: A Framework for Combating Adversarial Typos Erik Jones Robin Jia Aditi Raghunathan Percy Liang AAML 169 102 0 04 May 2020
GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding Alex Jinpeng Wang Amanpreet Singh Julian Michael Felix Hill Omer Levy Samuel R. Bowman ELM 316 7,044 0 20 Apr 2018
OpenNMT: Open-Source Toolkit for Neural Machine Translation Guillaume Klein Yoon Kim Yuntian Deng Jean Senellart Alexander M. Rush 276 1,897 0 10 Jan 2017
Effective Approaches to Attention-based Neural Machine Translation Thang Luong Hieu H. Pham Christopher D. Manning 225 7,939 0 17 Aug 2015