NAT: Noise-Aware Training for Robust Neural Sequence Labeling

14 May 2020

Papers citing "NAT: Noise-Aware Training for Robust Neural Sequence Labeling"

6 / 6 papers shown

Title
Revisit Input Perturbation Problems for LLMs: A Unified Robustness Evaluation Framework for Noisy Slot Filling Task Guanting Dong Jinxu Zhao Tingfeng Hui Daichi Guo Wenlong Wan ... Yueyan Qiu Zhuoma Gongque Keqing He Zechen Wang Weiran Xu AAML 35 20 0 10 Oct 2023
READIN: A Chinese Multi-Task Benchmark with Realistic and Diverse Input Noises Chenglei Si Zhengyan Zhang Yingfa Chen Xiaozhi Wang Zhiyuan Liu Maosong Sun AAML 26 1 0 14 Feb 2023
DialAug: Mixing up Dialogue Contexts in Contrastive Learning for Robust Conversational Modeling Lahari Poddar Peiyao Wang J. Reinspach 19 5 0 15 Apr 2022
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
TLDR9+: A Large Scale Resource for Extreme Summarization of Social Media Posts Sajad Sotudeh Hanieh Deilamsalehi Franck Dernoncourt Nazli Goharian 41 9 0 04 Oct 2021
Generating Natural Language Adversarial Examples M. Alzantot Yash Sharma Ahmed Elgohary Bo-Jhang Ho Mani B. Srivastava Kai-Wei Chang AAML 258 915 0 21 Apr 2018