Generalizability of Mixture of Domain-Specific Adapters from the Lens of Signed Weight Directions and its Application to Effective Model Pruning. - Tuc Nguyen; Thai Le (ACL (1), 2024)

Adapters Mixup: Mixing Parameter-Efficient Adapters to Enhance the Adversarial Robustness of Fine-tuned Pre-trained Text Classifiers. - Tuc Nguyen; Thai Le (EMNLP, 2024)

Marrying Adapters and Mixup to Efficiently Enhance the Adversarial Robustness of Pre-Trained Language Models for Text Classification. - Tuc Nguyen; Thai Le (CoRR, 2024)

NOMATTERXAI: Generating "No Matter What" Alterfactual Examples for Explaining Black-Box Text Classification Models. - Tuc Van Nguyen; James Michels; Hua Shen; Thai Le (AAAI, 2025)

Unraveling Interwoven Roles of Large Language Models in Authorship Privacy: Obfuscation, Mimicking, and Verification. - Tuc Nguyen; Yifan Hu; Thai Le (CoRR, 2025)