Publications

Training-Free Bayesianization for Low-Rank Adapters of Large Language Models

Estimating the uncertainty of responses of Large Language Models~(LLMs) remains a critical challenge. While recent Bayesian methods …

Haizhou Shi, Yibin Wang, Ligong Han, Dimitris Metaxas, Huan Zhang, Hao Wang

BLoB: Bayesian Low-Rank Adaptation by Backpropagation for Large Language Models

Large Language Models (LLMs) often suffer from overconfidence during inference, particularly when adapted to downstream domain-specific …

Yibin Wang, Haizhou Shi, Ligong Han, Dimitris Metaxas, Hao Wang

Continual Learning of Large Language Models: A Comprehensive Survey

‘The recent success of large language models (LLMs) trained on static, pre-collected, general datasets has sparked numerous …

Haizhou Shi, Zihao Xu, Hengyi Wang, Weiyi Qin, Wenyuan Wang, Yibin Wang, Hao Wang

Robustness-Aware Word Embedding Improves Certified Robustness to Adversarial Word Substitutions

Natural Language Processing (NLP) models have gained great success on clean texts, but they are known to be vulnerable to adversarial …

Yibin Wang, Yichen Yang, Di He, Kun He

Robustness-Aware Word Embedding Improves Certified Robustness to Adversarial Word Substitutions