4 citations · 6 across the 3 of their papers we have counts for
3 papers
cs.CV2023
Res-Attn : An Enhanced Res-Tuning Approach with Lightweight Attention Mechanism
Chaojie Mao, Zeyinzi Jiang
Res-Tuning introduces a flexible and efficient paradigm for model tuning, showing that tuners decoupled from the backbone network can achieve performance comparable to traditional…
cs.CV2023★ 4 cited
Res-Tuning: A Flexible and Efficient Tuning Paradigm via Unbinding Tuner from Backbone
Zeyinzi Jiang, Chaojie Mao, Ziyuan Huang +5
Parameter-efficient tuning has become a trend in transferring large-scale foundation models to downstream applications. Existing methods typically embed some light-weight tuners in…
cs.CV2023★ 2 cited
Rethinking Efficient Tuning Methods from a Unified Perspective
Zeyinzi Jiang, Chaojie Mao, Ziyuan Huang +3
Parameter-efficient transfer learning (PETL) based on large-scale pre-trained foundation models has achieved great success in various downstream applications. Existing tuning metho…