most citedHow Mask Matters: Towards Theoretical Understandings of Masked Autoencoders

20 citations · 23 across the 8 of their papers we have counts for

collaborators

8 papers

cs.CV2023

On the Generalization of Multi-modal Contrastive Learning

Qi Zhang, Yifei Wang, Yisen Wang

Multi-modal contrastive learning (MMCL) has recently garnered considerable interest due to its superior performance in visual tasks, achieved by embedding multi-modal data, such as…

cs.CL2023

Pre-training Language Model as a Multi-perspective Course Learner

Beiduo Chen, Shaohan Huang, Zihan Zhang +6

ELECTRA, the generator-discriminator pre-training framework, has achieved impressive semantic construction capability among various downstream tasks. Despite the convincing perform…

cs.LG2023

A Message Passing Perspective on Learning Dynamics of Contrastive Learning

Yifei Wang, Qi Zhang, Tianqi Du +3

In recent years, contrastive learning achieves impressive results on self-supervised visual representation learning, but there still lacks a rigorous understanding of its learning…

cs.CV2023★ 1 cited

PromptMix: Text-to-image diffusion models enhance the performance of lightweight networks

Arian Bakhtiarnia, Qi Zhang, Alexandros Iosifidis

Many deep learning tasks require annotations that are too time consuming for human operators, resulting in small dataset sizes. This is especially true for dense regression problem…

cs.CV2022

SLAN: Self-Locator Aided Network for Cross-Modal Understanding

Jiang-Tian Zhai, Qi Zhang, Tong Wu +4

Learning fine-grained interplay between vision and language allows to a more accurate understanding for VisionLanguage tasks. However, it remains challenging to extract key image r…

cs.CL2022

RAPO: An Adaptive Ranking Paradigm for Bilingual Lexicon Induction

Zhoujin Tian, Chaozhuo Li, Shuo Ren +8

Bilingual lexicon induction induces the word translations by aligning independently trained word embeddings in two languages. Existing approaches generally focus on minimizing the…

cs.LG2022★ 20 cited

How Mask Matters: Towards Theoretical Understandings of Masked Autoencoders

Qi Zhang, Yifei Wang, Yisen Wang

Masked Autoencoders (MAE) based on a reconstruction task have risen to be a promising paradigm for self-supervised learning (SSL) and achieve state-of-the-art performance across di…

cs.CV2022★ 2 cited

Exploring Anchor-based Detection for Ego4D Natural Language Query

Sipeng Zheng, Qi Zhang, Bei Liu +2

In this paper we provide the technique report of Ego4D natural language query challenge in CVPR 2022. Natural language query task is challenging due to the requirement of comprehen…