10 citations · 13 across the 6 of their papers we have counts for
4 papers · 1 filter
Layer-wise Representation Dynamics: An Empirical Investigation Across Embedders and Base LLMs
Jingzhou Jiang, Yi Yang, Kar Yan Tam
Hidden states change substantially across the layers of modern language models, but most layer-wise analyses focus on one aspect of that change. We propose Layer-wise Representatio…
Bi-level Personalization for Federated Foundation Models: A Task-vector Aggregation Approach
Yiyuan Yang, Guodong Long, Qinghua Lu +2
Federated foundation models represent a new paradigm to jointly fine-tune pre-trained foundation models across clients. It is still a challenge to fine-tune foundation models for a…
Federated Low-Rank Adaptation for Foundation Models: A Survey
Yiyuan Yang, Guodong Long, Qinghua Lu +3
Effectively leveraging private datasets remains a significant challenge in developing foundation models. Federated Learning (FL) has recently emerged as a collaborative framework t…
Federated Adapter on Foundation Models: An Out-Of-Distribution Approach
Yiyuan Yang, Guodong Long, Tianyi Zhou +3
As foundation models gain prominence, Federated Foundation Models (FedFM) have emerged as a privacy-preserving approach to collaboratively fine-tune models in federated learning (F…