Zhuokai Zhao
PhD Candidate in Computer Science
University of Chicago
Email / Google Scholar / Semantic Scholar / Github / LinkedIn / X (Twitter) / Resume

I am currently a Research Scientist at Meta AI. I got my PhD in Computer Science from the University of Chicago, where I was fortunate to have been working with Prof. Yuxin Chen, Prof. Bo Li, and Prof. Michael Maire. Prior to that, I received my Master's degree in Robotics from the Johns Hopkins University, under the supervision of Prof. Nassir Navab, and my Bachelor's degree with Honors in Electrical Engineering from the University of Illinois at Urbana-Champaign, where I was working with Prof. Seth Hutchinson.

My research interest is to develop novel algorithms that improve the trustworthiness, robustness, and data efficiency for multimodal deep learning models. More recently, I have been focusing on enhancing fairness, hallucinations reduction and reasoning capabilities for large language models (LLMs) and large vision-language models (LVLMs). At Meta AI, I also work on continued-pretraining and finetuning Llama as the next-gen recommender backbone.

Publications (* indicates co-first authorship)
MJ-BENCH: Is Your Multimodal Reward Model Really a Good Judge for Text-to-Image Generation?
Zhaorun Chen*, Yichao Du*, Zichen Wen*, Yiyang Zhou*, Chenhang Cui, Zhenzhen Weng, Haoqin Tu,
Chaoqi Wang, Zhengwei Tong, Qinglan Huang, Canyu Chen, Qinghao Ye, Zhihong Zhu, Yuqing Zhang, Jiawei Zhou,
Zhuokai Zhao, Rafael Rafailov, Chelsea Finn, and Huaxiu Yao
Preliminary version appeared in ICML Workshop on Foundation Models in the Wild, 2024
PDF / Code
RankCLIP: Ranking-Consistent Language-Image Pretraining
Yiming Zhang*, Zhuokai Zhao*, Zhaorun Chen, Zhili Feng, Zenghui Ding, and Yining Sun
In submission, 2024
PDF / Code
EscIRL: Evolving Self-Contrastive IRL for Trajectory Prediction in Autonomous Driving
Zhaorun Chen, Siyue Wang, Zhuokai Zhao, Chaoli Mao, Yiyang Zhou, Jiayu He, Sibo Hu
In submission, 2024
HALC: Object Hallucination Reduction via Adaptive Focal-Contrast Decoding
Zhaorun Chen*, Zhuokai Zhao*, Hongyin Luo, Huaxiu Yao, Bo Li, and Jiawei Zhou
International Conference on Machine Learning (ICML), 2024
Preliminary version appeared in ICLR Workshop on Reliable and Responsible Foundation Models
, 2024
PDF / Code
AutoPRM: Automating Procedural Supervision for Multi-Step Reasoning via Controllable Question Decomposition
Zhaorun Chen*, Zhuokai Zhao*, Zhihong Zhu*, Ruiqi Zhang, Xiang Li, Bhiksha Raj, and Huaxiu Yao
Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL), 2024
Preliminary version appeared in ICLR Workshop on Reliable and Responsible Foundation Models
, 2024
PDF / Code
Direct Acquisition Optimization for Low-Budget Active Learning
Zhuokai Zhao, Yibo Jiang, and Yuxin Chen
In submission, 2024
PDF / Code
RELAX: Reinforcement Learning Enabled 2D-LiDAR Autonomous System for Parsimonious UAVs
Guanlin Wu, Zhuokai Zhao, and Yutao He
In submission, 2023
PDF / Code

Multi-Modality Guidance Network For Missing Modality Inference
Zhuokai Zhao, Harish Palani, Tianyi Liu, Lena Evans, and Ruth Toner
IEEE International Conference on Multimedia and Expo (ICME), 2023
PDF / Code

Breaking the Curse of Quality Saturation with User-Centric Ranking
Zhuokai Zhao, Yang Yang, Wenjie Hu, and Shuang Yang
29th Conference on Knowledge Discovery and Data Mining (KDD), 2023
PDF / Code

Enhanced Data Utilization for Efficient and Trustworthy Deep Learning
Zhuokai Zhao
Ph.D. in Computer Science, 2024
Utilizing Both Past and Future: Multi-Frame Memory Based Network in Solving Particle Image Velocimetry
Zhuokai Zhao
MS in Computer Science, 2021
PDF / Code
Other Projects
Conference Reviewer Journal Reviewer

Last Updated: July 10, 2024