Assistant Professor, City University of Hong Kong
4 papers at NeurIPS 2025
We propose DEAL, a continual low-rank fine-tuning framework that enables efficient and privacy-preserving adaptation of large language models.
We built the first worldwide trajectory dataset and trained a universal trajectory foundation model.