Yifei Zhang | Emory University

About Me

Welcome! I’m Yifei Zhang, a second-year Ph.D. student in Computer Science at Emory University, where I have the fortune of working with Dr. Liang Zhao. Before this, I obtained my M.S. degree in Data Science from Columbia University and my B.E. degree in Engineering Mechanics from Dalian University of Technology. Additionally, I earned a Master of Engineering Management degree from Duke University.

My research encompasses Explainable AI, Natural Language Processing, and Applied Machine Learning. I hold a strong academic background and have contributed to multiple research projects, constantly pushing the boundaries of what’s possible in the data science field.

I have been actively looking for research scientist or applied scientist internship positions in Summer ~~2024~~ 2025. Feel free to reach out if there are any opportunities!

Research Interests

Explainable AI: Visual Explanation-guided Learning (Evaluating and Correcting the Reasoning of AI models)
Machine Learning: Weakly-Supervised Learning, Multi-modal Learning, Medical AI
Natural Language Processing: Multimodal Large Language Model, Explanation-guided Learning with Language Model

News

[Jul. 2024] One co-authored paper is accepted by CIKM 2024!
[May. 2024] One first-author paper is accepted by Findings of ACL 2024, and one co-authored paper is accepted by KDD 2024!
[May. 2024] I will join Amazon AGI team as a Research Scientist Intern at Boston in summer 2024!
[Apr. 2024] One first-author paper Visual Attention Prompted Prediction and Learning is accepted by IJCAI 2024!
[Apr. 2024] Taken on the role of Publicity Chair for the ACM SIGKDD Workshop on Deep Learning for Spatiotemporal Data, Applications, and Systems (DeepSpatial’24)
[Jan. 2024] Our survey paper Beyond Efficiency: A Systematic Survey of Resource-Efficient Large Language Models is available on Arxiv!
[Dec. 2023] One co-author paper is accepted by SDM 2024!
[Nov. 2023] Our work about Datasets and Benchmarks for Visual Explanation is available online!
[Aug. 2023] Taken Reviewer Invitations for IEEE Transactions on Neural Networks and Learning Systems.
[Jul. 2023] One first-author paper is accepted by ICCV 2023!
[May. 2023] One co-first-author paper is accepted by KDD 2023!

Selected publications and preprints

Arxiv

Beyond Efficiency: A Systematic Survey of Resource-Efficient Large Language Models

Guangji Bai, Zheng Chai, Chen Ling, Shiyu Wang, Jiaying Lu, Nan Zhang, Tingwei Shi, Ziyang Yu, Mengdan Zhu, Yifei Zhang, Carl Yang, Yue Cheng, Liang Zhao

Arxiv

PDF Page

Arxiv

XAI Benchmark for Visual Explanation

Yifei Zhang, Siyi Gu, James Song, Bo Pan, Guangji Bai, Liang Zhao

Arxiv

PDF Page

KDD'24

DUE: Dynamic Uncertainty-Aware Explanation Supervision via 3D Imputation

Qilong Zhao, Yifei Zhang, Mengdan Zhu, Siyi Gu, Yuyang Gao, Xiaofeng Yang, Liang Zhao

The 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2024.

PDF

CIKM' 24

Distilling Large Language Models for Text-Attributed Graph Learning

Bo Pan, Zheng Zhang, Yifei Zhang, Yuntong Hu, Liang Zhao

The 33rd ACM International Conference on Information and Knowledge Management (CIKM), 2024.

PDF

ACL' 24

ELAD: Explanation-Guided Large Language Models Active Distillation

Yifei Zhang, Bo Pan, Chen Ling, Yuntong Hu, Liang Zhao

The 62nd Annual Meeting of the Association for Computational Linguistics (ACL-Findings), 2024.

PDF Poster

IJCAI' 24

Visual Attention Prompted Prediction and Learning

Yifei Zhang, Bo Pan, Siyi Gu, Guangji Bai, Meikang Qiu, Xiaofeng Yang, Liang Zhao

International Joint Conference on Artificial Intelligence (IJCAI), 2024.

PDF Page

SDM' 24

STES: A Spatiotemporal Explanation Supervision Framework

Dazhou Yu, Binbin Chen, Yun Li, Suman Dhaka, Yifei Zhang, Zhenke Liu, Minxing Zhang, Jie Zhang, Liang Zhao

SIAM International Conference on Data Mining (SDM), 2024.

PDF

ICCV'23

MAGI: Multi-Annotated Explanation-Guided Learning

Yifei Zhang, Siyi Gu, Yuyang Gao, Bo Pan, Xiaofeng Yang, Liang Zhao

The IEEE/CVF International Conference on Computer Vision (ICCV), 2023.

PDF

KDD'23

ESSA: Explanation Iterative Supervision via Saliency-guided Data Augmentation

Siyi Gu*, Yifei Zhang*, Yuyang Gao, Xiaofeng Yang, Liang Zhao (* denotes equal contribution)

The 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2023.

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Education Experience

	Emory University, 2022.08- Ph.D. in Computer Science
	Columbia University, 2020.09-2021.12 M.S. in Data Science
	Duke University, 2019.08-2020.05 Master of Engineering Management
	Dalian University of Technology, 2015.09-2019.06 B.E. in Engineering Mechanics (Excellence Program)

Internship Experience

	Amazon AGI, 2024.06-2024.09 Research Scientist Intern
	Guotai Junan Securities, 2018.12-2019.03 Equity Research Intern
	China Development Bank, 2018.01-2018.03 Risk Management Intern

Services

Journal Reviewers

Workshop Organizers

Publicity Chair for 4th ACM SIGKDD Workshop on Deep Learning for Spatiotemporal Data, Applications, and Systems (DeepSpatial’24)

Awards

KDD 2023 Student Travel Award
DUTOAA Seagle Scholarship Award, DUTOAA Foundation
Academic Excellence Scholarship Award, Dalian University of Technology
Technological Innovation Scholarship Award, Dalian University of Technology

Softwares

XAI Benchmark for Visual Explanation: A benchmark for visual explanation that comprising eight diverse datasets with human annotations and offering a comprehensive evaluation pipeline with alignment-based and faithfulness-based metrics. More information is available on the project website.
Group-Specific Recommendation System (GSRS): A group-specific recommendation system to use dependency information from users and items which share similar characteristics under the singular value decomposition framework. This project was a collaboration with Dr. Xuan Bi at the University of Minnesota (UMN). For more details, visit the GSRS package on CRAN.