no code implementations • CONSTRAINT (ACL) 2022 • Jason Lucas, Limeng Cui, Thai Le, Dongwon Lee
The COVID-19 pandemic has created threats to global health control.
no code implementations • EMNLP 2020 • Adaku Uchendu, Thai Le, Kai Shu, Dongwon Lee
In recent years, the task of generating realistic short and long texts have made tremendous advancements.
1 code implementation • Findings (ACL) 2022 • Thai Le, Jooyoung Lee, Kevin Yen, Yifan Hu, Dongwon Lee
We find that adversarial texts generated by ANTHRO achieve the best trade-off between (1) attack success rate, (2) semantic preservation of the original text, and (3) stealthiness--i. e. indistinguishable from human writings hence harder to be flagged as suspicious.
no code implementations • 15 Mar 2022 • Jooyoung Lee, Thai Le, Jinghui Chen, Dongwon Lee
Past literature has illustrated that language models do not fully understand the context and sensitivity of text and can sometimes memorize phrases or sentences present in their training sets.
no code implementations • 20 Oct 2021 • Thai Le, Long Tran-Thanh, Dongwon Lee
To this question, we successfully demonstrate that indeed it is possible for adversaries to exploit computational learning mechanism such as reinforcement learning (RL) to maximize the influence of socialbots while avoiding being detected.
no code implementations • Findings (EMNLP) 2021 • Adaku Uchendu, Zeyu Ma, Thai Le, Rui Zhang, Dongwon Lee
Recent progress in generative language models has enabled machines to generate astonishingly realistic texts.
no code implementations • 31 May 2021 • Duanshun Li, Jing Liu, Jinsung Jeon, Seoyoung Hong, Thai Le, Dongwon Lee, Noseong Park
On top of the prediction models, we define a budget-constrained flight frequency optimization problem to maximize the market influence over 2, 262 routes.
no code implementations • ACL 2021 • Thai Le, Noseong Park, Dongwon Lee
The Universal Trigger (UniTrigger) is a recently-proposed powerful adversarial textual attack method.
1 code implementation • ACL 2022 • Thai Le, Noseong Park, Dongwon Lee
Even though several methods have proposed to defend textual neural network (NN) models against black-box adversarial attacks, they often defend against a specific text perturbation strategy and/or require re-training the models from scratch.
1 code implementation • 1 Sep 2020 • Thai Le, Suhang Wang, Dongwon Lee
In recent years, the proliferation of so-called "fake news" has caused much disruptions in society and weakened the news ecosystem.
1 code implementation • 5 Nov 2019 • Thai Le, Suhang Wang, Dongwon Lee
Despite the recent development in the topic of explainable AI/ML for image and text data, the majority of current solutions are not suitable to explain the prediction of neural network models when the datasets are tabular and their features are in high-dimensional vectorized formats.
no code implementations • 5 Oct 2017 • Xinyue Cao, Thai Le, Jason, Zhang
In this paper, we make use of a dataset from the clickbait challenge 2017 (clickbait-challenge. com) comprising of over 21, 000 headlines/titles, each of which is annotated by at least five judgments from crowdsourcing on how clickbait it is.