activity
20172022
most citedCATER: Intellectual Property Protection on Text Generation APIs via Conditional Watermarks

19 citations · 35 across the 5 of their papers we have counts for

collaborators

7 papers

cs.CR2022

Extracted BERT Model Leaks More Information than You Think!

Xuanli He, Chen Chen, Lingjuan Lyu +1

The collection and availability of big data, combined with advances in pre-trained models (e.g. BERT), have revolutionized the predictive performance of natural language processing…

cs.CR202219 cited

CATER: Intellectual Property Protection on Text Generation APIs via Conditional Watermarks

Xuanli He, Qiongkai Xu, Yi Zeng +4

Previous works have validated that text generation APIs can be stolen through imitation attacks, causing IP violations. In order to protect the IP of text generation APIs, a recent…

cs.LG2021

Humanly Certifying Superhuman Classifiers

Qiongkai Xu, Christian Walder, Chenchen Xu

Estimating the performance of a machine learning system is a longstanding challenge in artificial intelligence research. Today, this challenge is especially relevant given the emer…

cs.CL20216 cited

Model Extraction and Adversarial Transferability, Your BERT is Vulnerable!

Xuanli He, Lingjuan Lyu, Qiongkai Xu +1

Natural language processing (NLP) tasks, ranging from text classification to text generation, have been revolutionised by the pre-trained language models, such as BERT. This allows…

cs.CL2019

ALTER: Auxiliary Text Rewriting Tool for Natural Language Generation

Qiongkai Xu, Chenchen Xu, Lizhen Qu

In this paper, we describe ALTER, an auxiliary text rewriting tool that facilitates the rewriting process for natural language generation tasks, such as paraphrasing, text simplifi…

cs.CL2018

D-PAGE: Diverse Paraphrase Generation

Qiongkai Xu, Juyan Zhang, Lizhen Qu +2

In this paper, we investigate the diversity aspect of paraphrase generation. Prior deep learning models employ either decoding methods or add random input noise for varying outputs…