1 citations · 1 across the 3 of their papers we have counts for
3 papers
cs.LG2024
Learning and Transferring Sparse Contextual Bigrams with Linear Transformers
Yunwei Ren, Zixuan Wang, Jason D. Lee
Transformers have excelled in natural language modeling and one reason behind this success is their exceptional ability to combine contextual informal and global knowledge. However…
cs.LG2023★ 1 cited
On the Importance of Contrastive Loss in Multimodal Learning
Yunwei Ren, Yuanzhi Li
Recently, contrastive learning approaches (e.g., CLIP (Radford et al., 2021)) have received huge success in multimodal learning, where the model tries to minimize the distance betw…
cs.LG2023
Depth Separation with Multilayer Mean-Field Networks
Yunwei Ren, Mo Zhou, Rong Ge
Depth separation -- why a deeper network is more powerful than a shallower one -- has been a major problem in deep learning theory. Previous results often focus on representation p…