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Thai Le
Thai Le
Assistant Professor, Indiana University
Verified email at iu.edu - Homepage
Title
Cited by
Cited by
Year
“Fake News” Is Not Simply False Information: A Concept Explication and Taxonomy of Online Content
MD Molina, SS Sundar, T Le, D Lee
American Behavioral Scientist, 2019
4832019
Authorship Attribution for Neural Text Generation
A Uchendu, T Le, K Shu, D Lee
The 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP), 2020
1412020
Deep Headline Generation for Clickbait Detection
K Shu, S Wang, T Le, D Lee, H Liu
2018 IEEE International Conference on Data Mining (ICDM), 467-476, 2018
752018
MALCOM: Generating Malicious Comments to Attack Neural Fake News Detection Models
T Le, S Wang, D Lee
2020 IEEE International Conference on Data Mining (ICDM), 2020
682020
GRACE: Generating Concise and Informative Contrastive Sample to Explain Neural Network Model's Prediction
T Le, S Wang, D Lee
26th ACM SIGKDD International Conference on Knowledge Discovery & Data …, 2020
672020
TURINGBENCH: A Benchmark Environment for Turing Test in the Age of Neural Text Generation
A Uchendu, Z Ma, T Le, R Zhang, D Lee
The 2021 Conference on Empirical Methods in Natural Language Processing (EMNLP), 2021
622021
Do Language Models Plagiarize?
J Lee, T Le, J Chen, D Lee
The 2023 ACM Web Conference, 2023
522023
An Innovative Tour Recommendation System For Tourists In Japan
Q Thai LE, D PISHVA
The 17th International Conference on Advanced Communications Technology …, 2015
37*2015
A Sweet Rabbit Hole by DARCY: Using Honeypots to Detect Universal Trigger’s Adversarial Attacks
T Le, N Park, D Lee
59th Annual Meeting of the Association for Computational Linguistics (ACL), 2021
29*2021
Machine Learning Based Detection of Clickbait Posts in Social Media
X Cao, T Le
arXiv preprint arXiv:1710.01977, 2017
292017
Does Clickbait Actually Attract More Clicks? Three Clickbait studies you must read
M Molina, SS Sundar, MMU Rony, N Hassan, T Le, D Lee
2021 ACM Conference on Human Factors in Computing Systems, 2021
272021
Perturbations in the Wild: Leveraging Human-Written Text Perturbations for Realistic Adversarial Attack and Defense
T Le, J Lee, K Yen, Y Hu, D Lee
Annual Meeting of the Association for Computational Linguistics (ACL) (Findings), 2022
262022
Attribution and Obfuscation of Neural Text Authorship: A Data Mining Perspective
A Uchendu, T Le, D Lee
SIGKDD Explorations 25, 2023
242023
How Gullible are You? Predicting Susceptibility to Fake News
TJ Shen, R Cowell, A Gupta, T Le, A Yadav, D Lee
Proceedings of the 10th ACM Conference on Web Science, 287-288, 2019
212019
A Machine Learning Framework For Automating Well Log Depth Matching
L Liang, T Le, T Zimmermann, S Zeroug, D Heliot
SPWLA Annual Logging Symposium, D033S003R009, 2019
212019
SHIELD: Defending Textual Neural Networks against Multiple Black-Box Adversarial Attacks with Stochastic Multi-Expert Patcher
T Le, N Park, D Lee
Proceedings of the 60th Annual Meeting of the Association for Computational …, 2022
192022
A Machine-learning Framework For Automating Well-log Depth Matching
T Le, L Liang, T Zimmermann, S Zeroug, D Heliot
Petrophysics 60 (05), 585-595, 2019
16*2019
Application Of Artificial Neural Network In Social Media Data Analysis: A Case Of Lodging Business In Philadelphia
T Le, P Pardo, W Claster
Artificial Neural Network Modelling, 369-376, 2016
162016
MULTITuDE: Large-Scale Multilingual Machine-Generated Text Detection Benchmark
D Macko, R Moro, A Uchendu, JS Lucas, M Yamashita, M Pikuliak, I Srba, ...
The 2023 Conference on Empirical Methods in Natural Language Processing, 2023
142023
Socialbots on Fire: Modeling Adversarial Behaviors of Socialbots via Multi-Agent Hierarchical Reinforcement Learning
T Le, L Tran-Thanh, D Lee
Proceedings of the ACM Web Conference 2022, 2022
112022
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Articles 1–20