no code implementations • 21 Feb 2024 • Zichang Liu, Qingyun Liu, Yuening Li, Liang Liu, Anshumali Shrivastava, Shuchao Bi, Lichan Hong, Ed H. Chi, Zhe Zhao
Further, to accommodate the dissimilarity among the teachers in the committee, we introduce DiverseDistill, which allows the student to understand the expertise of each teacher and extract task knowledge.
no code implementations • 7 Feb 2024 • Yuji Roh, Qingyun Liu, Huan Gui, Zhe Yuan, Yujin Tang, Steven Euijong Whang, Liang Liu, Shuchao Bi, Lichan Hong, Ed H. Chi, Zhe Zhao
By combining two complementing models, LEVI effectively suppresses problematic features in both the fine-tuning data and pre-trained model and preserves useful features for new tasks.
no code implementations • 4 Oct 2023 • Zhe Zhao, Qingyun Liu, Huan Gui, Bang An, Lichan Hong, Ed H. Chi
In this paper, we extend KD with an interactive communication process to help students of downstream tasks learn effectively from pre-trained foundation models.