Lee, Dongwon

“Fake News” Is Not Simply False Information: A Concept Explication and Taxonomy of Online Content

Molina, M. D., Sundar, S. S., Le, T., & Lee, D. (2021) · American Behavioral Scientist

Misinformation and Its ImpactsSpam and Phishing Detection

Cited by 485

Authorship Attribution for Neural Text Generation

Uchendu, A., Le, T., Shu, K., & Lee, D. (2020) · Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)

Authorship Attribution and ProfilingTopic Modeling

Cited by 120

TURINGBENCH: A Benchmark Environment for Turing Test in the Age of Neural Text Generation

Uchendu, A., Ma, Z., Le, T., Zhang, R., & Lee, D. (2021) · Findings of the Association for Computational Linguistics: EMNLP 2021

Authorship Attribution and ProfilingTopic Modeling

Cited by 82

Do Language Models Plagiarize?

Lee, J., Le, T., Chen, J., & Lee, D. (2023) · Proceedings of the ACM Web Conference 2023

Topic ModelingAcademic integrity and plagiarism

Cited by 51

Do Language Models Plagiarize?

Lee, J., Le, T., Chen, J., & Lee, D. (2022) · arXiv

Topic ModelingAcademic integrity and plagiarism

Cited by 51

MathBERT: A Pre-trained Language Model for General NLP Tasks in Mathematics Education

Shen, J. T., Yamashita, M., Prihar, E., Heffernan, N., Wu, X., Graff, B., & Lee, D. (2021) · arXiv

Topic ModelingIntelligent Tutoring Systems and Adaptive Learning

Cited by 47

Uncovering Fake Likers in Online Social Networks

Badri Satya, P. R., Lee, K., Lee, D., Tran, T., & Zhang, J. (. (2016) · Proceedings of the 25th ACM International on Conference on Information and Knowledge Management

Spam and Phishing DetectionMisinformation and Its Impacts

Cited by 46

Multitude: Large-scale multilingual machine-generated text detection benchmark

Macko, D., Moro, R., Uchendu, A., Lucas, J., Yamashita, M., Pikuliak, M., Srba, I., Le, T., Lee, D., Simko, J., et al. (2023) · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing

Natural Language Processing TechniquesAuthorship Attribution and Profiling

Cited by 38

Fighting Fire with Fire: The Dual Role of LLMs in Crafting and Detecting Elusive Disinformation

Lucas, J., Uchendu, A., Yamashita, M., Lee, J., Rohatgi, S., & Lee, D. (2023) · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing

Misinformation and Its ImpactsSpam and Phishing Detection

Cited by 37

GPT-who: An Information Density-based Machine-Generated Text Detector

Venkatraman, S., Uchendu, A., & Lee, D. (2023) · arXiv

Authorship Attribution and ProfilingDigital Media Forensic Detection

Cited by 21

HANSEN: Human and AI Spoken Text Benchmark for Authorship Analysis

Tripto, N., Uchendu, A., Le, T., Setzu, M., Giannotti, F., & Lee, D. (2023) · Findings of the Association for Computational Linguistics: EMNLP 2023

Authorship Attribution and ProfilingSpeech Recognition and Synthesis

Cited by 6

HANSEN: Human and AI Spoken Text Benchmark for Authorship Analysis

Tripto, N. I., Uchendu, A., Le, T., Setzu, M., Giannotti, F., & Lee, D. (2023) · arXiv

Authorship Attribution and ProfilingSpeech Recognition and Synthesis

Cited by 6

Authorship Obfuscation in Multilingual Machine-Generated Text Detection

Macko, D., Moro, R., Uchendu, A., Srba, I., Lucas, J. S., Yamashita, M., Tripto, N. I., Lee, D., Simko, J., & Bielikova, M. (2024) · arXiv

Authorship Attribution and ProfilingNatural Language Processing Techniques

Cited by 6