Thai Le
Orcid: 0000-0001-9632-6870
According to our database1,
Thai Le
authored at least 63 papers
between 2011 and 2024.
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Bibliography
2024
CoRR, 2024
NoMatterXAI: Generating "No Matter What" Alterfactual Examples for Explaining Black-Box Text Classification Models.
CoRR, 2024
PlagBench: Exploring the Duality of Large Language Models in Plagiarism Generation and Detection.
CoRR, 2024
Beyond Individual Facts: Investigating Categorical Knowledge Locality of Taxonomy and Meronomy Concepts in GPT Models.
CoRR, 2024
The Effect of Similarity Measures on Accurate Stability Estimates for Local Surrogate Models in Text-based Explainable AI.
CoRR, 2024
Marrying Adapters and Mixup to Efficiently Enhance the Adversarial Robustness of Pre-Trained Language Models for Text Classification.
CoRR, 2024
The Strange Case of Jekyll and Hyde: Analysis of R/ToastMe and R/RoastMe Users on Reddit.
Proceedings of the Eighteenth International AAAI Conference on Web and Social Media, 2024
Adapters Mixup: Mixing Parameter-Efficient Adapters to Enhance the Adversarial Robustness of Fine-tuned Pre-trained Text Classifiers.
Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024
TopFormer: Topology-Aware Authorship Attribution of Deepfake Texts with Diverse Writing Styles.
Proceedings of the ECAI 2024 - 27th European Conference on Artificial Intelligence, 19-24 October 2024, Santiago de Compostela, Spain, 2024
Proceedings of the Artificial Intelligence in Education - 25th International Conference, 2024
Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2024
Generalizability of Mixture of Domain-Specific Adapters from the Lens of Signed Weight Directions and its Application to Effective Model Pruning.
Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2024
A Curious Case of Searching for the Correlation between Training Data and Adversarial Robustness of Transformer Textual Models.
Proceedings of the Findings of the Association for Computational Linguistics, 2024
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024
Benchmarking Machine Learning Techniques for Bankruptcy Prediction under Benign and Adversarial Behaviors.
Proceedings of the 2024 ACM Southeast Conference, 2024
Proceedings of the 2024 ACM Southeast Conference, 2024
2023
A novel policy-graph approach with natural language and counterfactual abstractions for explaining reinforcement learning agents.
Auton. Agents Multi Agent Syst., October, 2023
SIGKDD Explor., 2023
Are Your Explanations Reliable? Investigating the Stability of LIME in Explaining Textual Classification Models via Adversarial Perturbation.
CoRR, 2023
CoRR, 2023
NoisyHate: Benchmarking Content Moderation Machine Learning Models with Human-Written Perturbations Online.
CoRR, 2023
Proceedings of the Companion Proceedings of the ACM Web Conference 2023, 2023
CrypText: Database and Interactive Toolkit of Human-Written Text Perturbations in the Wild.
Proceedings of the 39th IEEE International Conference on Data Engineering, 2023
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023
Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023
"Are Your Explanations Reliable?" Investigating the Stability of LIME in Explaining Text Classifiers by Marrying XAI and Adversarial Attack.
Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023
2022
Socialbots on Fire: Modeling Adversarial Behaviors of Socialbots via Multi-Agent Hierarchical Reinforcement Learning.
Proceedings of the WWW '22: The ACM Web Conference 2022, Virtual Event, Lyon, France, April 25, 2022
CAPS: Comprehensible Abstract Policy Summaries for Explaining Reinforcement Learning Agents.
Proceedings of the 21st International Conference on Autonomous Agents and Multiagent Systems, 2022
SHIELD: Defending Textual Neural Networks against Multiple Black-Box Adversarial Attacks with Stochastic Multi-Expert Patcher.
Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2022
Perturbations in the Wild: Leveraging Human-Written Text Perturbations for Realistic Adversarial Attack and Defense.
Proceedings of the Findings of the Association for Computational Linguistics: ACL 2022, 2022
2021
Adversarial Socialbot Learning via Multi-Agent Deep Hierarchical Reinforcement Learning.
CoRR, 2021
Proceedings of the Machine Learning and Knowledge Discovery in Databases. Applied Data Science Track, 2021
Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021
TURINGBENCH: A Benchmark Environment for Turing Test in the Age of Neural Text Generation.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2021, 2021
Proceedings of the CHI '21: CHI Conference on Human Factors in Computing Systems, 2021
A Sweet Rabbit Hole by DARCY: Using Honeypots to Detect Universal Trigger's Adversarial Attacks.
Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing, 2021
2020
GRACE: Generating Concise and Informative Contrastive Sample to Explain Neural Network Model's Prediction.
Proceedings of the KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2020
Proceedings of the 20th IEEE International Conference on Data Mining, 2020
Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, 2020
2019
Why X rather than Y? Explaining Neural Model' Predictions by Generating Intervention Counterfactual Samples.
CoRR, 2019
Proceedings of the 11th ACM Conference on Web Science, 2019
PATHFINDER: Graph-Based Itemset Embedding for Learning Course Recommendation and Beyond.
Proceedings of the 2019 International Conference on Data Mining Workshops, 2019
5 sources of clickbaits you should know!: using synthetic clickbaits to improve prediction and distinguish between bot-generated and human-written headlines.
Proceedings of the ASONAM '19: International Conference on Advances in Social Networks Analysis and Mining, 2019
2018
Proceedings of the IEEE International Conference on Data Mining, 2018
2017
2016
IEEE Computer Graphics and Applications, 2016
2015
The use of think-aloud and instant data analysis in evaluation research: Exemplar and lessons learned.
J. Biomed. Informatics, 2015
Fingerprinting Biomedical Terminologies - Automatic Classification and Visualization of Biomedical Vocabularies through UMLS Semantic Group Profiles.
Proceedings of the MEDINFO 2015: eHealth-enabled Health, 2015
Proceedings of the MEDINFO 2015: eHealth-enabled Health, 2015
2014
J. Biomed. Informatics, 2014
2013
Int. J. Medical Informatics, 2013
Comparing Information Needs of Health Care Providers and Older Adults: Findings from a Wellness Study.
Proceedings of the MEDINFO 2013, 2013
Proceedings of the MEDINFO 2013, 2013
Proceedings of the AMIA 2013, 2013
2012
Int. J. Electron. Heal., 2012
Administering a Wide-Scale Survey to Community Dwelling Older Adults: Implications and Lessons Learned.
Proceedings of the AMIA 2012, 2012
2011
Facial Expression Classification Based on Multi Artificial Neural Network and Two Dimensional Principal Component Analysis
CoRR, 2011