AI-secure / InfoBERT

[ICLR 2021] "InfoBERT: Improving Robustness of Language Models from An Information Theoretic Perspective" by Boxin Wang, Shuohang Wang, Yu Cheng, Zhe Gan, Ruoxi Jia, Bo Li, Jingjing Liu

InfoBERT: Improving Robustness of Language Models from An Information Theoretic Perspective

This is the official code base for our ICLR 2021 paper:

"InfoBERT: Improving Robustness of Language Models from An Information Theoretic Perspective".

Boxin Wang, Shuohang Wang, Yu Cheng, Zhe Gan, Ruoxi Jia, Bo Li, Jingjing Liu

Usage

Prepare your environment

Download required packages

pip install -r requirements.txt

ANLI and TextFooler

To run ANLI and TextFooler experiments, refer to README in the ANLI directory.

SQuAD

To run SQuAD experiments, refer to README in the SQuAD directory.

Citation

@inproceedings{
wang2021infobert,
title={InfoBERT: Improving Robustness of Language Models from An Information Theoretic Perspective},
author={Wang, Boxin and Wang, Shuohang and Cheng, Yu and Gan, Zhe and Jia, Ruoxi and Li, Bo and Liu, Jingjing},
booktitle={International Conference on Learning Representations},
year={2021}}