Zhiqiang Tang

About Zhiqiang Tang

Zhiqiang Tang, With an exceptional h-index of 12 and a recent h-index of 12 (since 2020), a distinguished researcher at Rutgers, The State University of New Jersey, specializes in the field of AutoML, EfficientML, RobustML.

His recent articles reflect a diverse array of research interests and contributions to the field:

AutoGluon-Multimodal (AutoMM): Supercharging Multimodal AutoML with Foundation Models

Convolution Meets LoRA: Parameter Efficient Finetuning for Segment Anything Model

Benchmarking Robustness of Multimodal Image-Text Models under Distribution Shift

Learning Multimodal Data Augmentation in Feature Space

Are Multimodal Models Robust to Image and Text Perturbations?

Benchmarking robustness under distribution shift of multimodal image-text models

Visual prompt tuning for test-time domain adaptation

Enabling data diversity: efficient automatic augmentation via regularized adversarial training

Zhiqiang Tang Information

University

Position

Ph.D. Student Department of Computer Science .

Citations(all)

921

Citations(since 2020)

878

Cited By

385

hIndex(all)

12

hIndex(since 2020)

12

i10Index(all)

17

i10Index(since 2020)

13

Email

University Profile Page

Google Scholar

Zhiqiang Tang Skills & Research Interests

AutoML

EfficientML

RobustML

Top articles of Zhiqiang Tang

AutoGluon-Multimodal (AutoMM): Supercharging Multimodal AutoML with Foundation Models

arXiv preprint arXiv:2404.16233

2024/4/24

Convolution Meets LoRA: Parameter Efficient Finetuning for Segment Anything Model

arXiv preprint arXiv:2401.17868

2024/1/31

Benchmarking Robustness of Multimodal Image-Text Models under Distribution Shift

Journal of Data-centric Machine Learning Research

2023/11/3

Learning Multimodal Data Augmentation in Feature Space

arXiv preprint arXiv:2212.14453

2022/12/29

Are Multimodal Models Robust to Image and Text Perturbations?

arXiv preprint arXiv:2212.08044

2022/12/15

Benchmarking robustness under distribution shift of multimodal image-text models

2022/10/21

Visual prompt tuning for test-time domain adaptation

arXiv preprint arXiv:2210.04831

2022/10/10

Enabling data diversity: efficient automatic augmentation via regularized adversarial training

2021/6/14

Crossnorm and selfnorm for generalization under distribution shifts

2021

Efficient and Robust Deep Learning

2021

Zhiqiang Tang
Zhiqiang Tang

H-Index: 9

OnlineAugment: Online data augmentation with less domain knowledge

2020/7/17

Zhiqiang Tang
Zhiqiang Tang

H-Index: 9

Yunhe Gao
Yunhe Gao

H-Index: 4

See List of Professors in Zhiqiang Tang University(Rutgers, The State University of New Jersey)