Robust Machine Comprehension Models via Adversarial Training

17 April 2018

Papers citing "Robust Machine Comprehension Models via Adversarial Training"

22 / 22 papers shown

Title
Contextual Breach: Assessing the Robustness of Transformer-based QA Models Asir Saadat Nahian Ibn Asad Md Farhan Ishmam AAML 46 0 0 17 Sep 2024
Specification Overfitting in Artificial Intelligence Benjamin Roth Pedro Henrique Luz de Araujo Yuxi Xia Saskia Kaltenbrunner Christoph Korab 58 0 0 13 Mar 2024
No offence, Bert -- I insult only humans! Multiple addressees sentence-level attack on toxicity detection neural network Sergey Berezin R. Farahbakhsh Noel Crespi 13 0 0 19 Oct 2023
A Survey of Safety and Trustworthiness of Large Language Models through the Lens of Verification and Validation Xiaowei Huang Wenjie Ruan Wei Huang Gao Jin Yizhen Dong ... Sihao Wu Peipei Xu Dengyu Wu André Freitas Mustafa A. Mustafa ALM 39 82 0 19 May 2023
Evaluating the Robustness of Machine Reading Comprehension Models to Low Resource Entity Renaming Clemencia Siro T. Ajayi 20 2 0 06 Apr 2023
Data Augmentation for Neural NLP Domagoj Pluscec Jan Snajder 16 6 0 22 Feb 2023
Improving Lexical Embeddings for Robust Question Answering Weiwen Xu Bowei Zou Wai Lam A. Aw OOD AAML 21 1 0 28 Feb 2022
CLLD: Contrastive Learning with Label Distance for Text Classification Jinhe Lan Qingyuan Zhan Chenhao Jiang Kunping Yuan Desheng Wang VLM 34 2 0 25 Oct 2021
Virtual Data Augmentation: A Robust and General Framework for Fine-tuning Pre-trained Models Kun Zhou Wayne Xin Zhao Sirui Wang Fuzheng Zhang Wei Yu Wu Ji-Rong Wen AAML 21 7 0 13 Sep 2021
CLINE: Contrastive Learning with Semantic Negative Examples for Natural Language Understanding Dong Wang Ning Ding Pijian Li Haitao Zheng AAML 37 115 0 01 Jul 2021
An Empirical Survey of Data Augmentation for Limited Data Learning in NLP Jiaao Chen Derek Tam Colin Raffel Joey Tianyi Zhou Diyi Yang 28 172 0 14 Jun 2021
Contrastive Fine-tuning Improves Robustness for Neural Rankers Xiaofei Ma Cicero Nogueira dos Santos Andrew O. Arnold 13 20 0 27 May 2021
Can NLI Models Verify QA Systems' Predictions? Jifan Chen Eunsol Choi Greg Durrett 23 54 0 18 Apr 2021
Are Multilingual BERT models robust? A Case Study on Adversarial Attacks for Multilingual Question Answering Sara Rosenthal Mihaela A. Bornea Avirup Sil AAML 31 10 0 15 Apr 2021
Counterfactual Variable Control for Robust and Interpretable Question Answering S. Yu Yulei Niu Shuohang Wang Jing Jiang Qianru Sun AAML OOD 42 9 0 12 Oct 2020
Frequency-Guided Word Substitutions for Detecting Textual Adversarial Examples Maximilian Mozes Pontus Stenetorp Bennett Kleinberg Lewis D. Griffin AAML 25 99 0 13 Apr 2020
A Survey on Machine Reading Comprehension Systems Razieh Baradaran Razieh Ghiasi Hossein Amirkhani FaML 13 85 0 06 Jan 2020
Stance Detection Benchmark: How Robust Is Your Stance Detection? Benjamin Schiller Johannes Daxenberger Iryna Gurevych 11 95 0 06 Jan 2020
Improving Machine Reading Comprehension via Adversarial Training Ziqing Yang Yiming Cui Wanxiang Che Ting Liu Shijin Wang Guoping Hu 27 17 0 09 Nov 2019
Adversarial Attacks on Deep Learning Models in Natural Language Processing: A Survey W. Zhang Quan Z. Sheng A. Alhazmi Chenliang Li AAML 24 57 0 21 Jan 2019
Attention-Guided Answer Distillation for Machine Reading Comprehension Minghao Hu Yuxing Peng Furu Wei Zhen Huang Dongsheng Li Nan Yang M. Zhou FaML 21 75 0 23 Aug 2018
Adversarial Machine Learning at Scale Alexey Kurakin Ian Goodfellow Samy Bengio AAML 264 3,110 0 04 Nov 2016