I am a 3rd-year undergraduate in Mathematics and Computer Science at Arcadia University, currently collaborating with Prof. Zhengzhong Tu at Texas A&M University and Prof. Yue Zhao at USC on Reasoning and Alignment for Multimodal Large Language Models (MLLMs). Previously, I worked with Prof. Zhe Liu, and Prof. Victor S. Sheng on research in Robust Medical Vision and Multimodal Machine Learning. Moving forward, I am eager to continue exploring the magic of Large Vision-Language Models.

Research Interests

My long-term vision is to develop efficient, robust and generalizable machine learning system capable of perceiving, understanding and interacting with the world through multimodal information from both 2D and 3D perspectives. Specifically, my previous research focuses on these topics:

Generalizable Medical Image Segmentation with Sparse and Noisy Labeled Data
Modality Competition and Imbalances for Multimodal Machine Learning
Cross-modal Decoupling and Alignment for Multimodal Representation Learning
Reasoning and Alignment for Large Vision-language Models

🔥 News

2025.03: 🎉🎉 Excited to propose my first-author work DecAlign, a novel cross-modal decoupling and alignment framwork for multimodal representation learning, which is now available on ArXiv!
2025.02: 🎉🎉 Excited to propose Re-Align, a novel alignment framework that leverages image retrieval to mitigate hallucinations in Vision Language Models, which is now available on ArXiv!
2025.01: 🎉🎉 I will collaborate with Prof. Zhengzhong Tu on advancing cutting-edge research in the alignment of Multimodal Foundation Models and Multimodal Large Language Models (MLLMs)！
2024.11: 🎉🎉 Excited to propose my first-author work DynCIM, a novel dynamic multimodal curriculum learning framework in addressing cross-modal competition and imbalances, which is now available on ArXiv!
2024.11: 🎉🎉 My co-authored paper is now under Major Revision by IEEE Transaction on Medical Imaging (IF: 8.9).
2024.10: 🎉🎉 My co-authored paper is now under Major Revision by Medical Image Analysis (IF: 10.9).
2024.08: 🎉🎉 Excited to propose my first-author work ALC, a novel adaptive label correction framework for medical image segmentation with noisy labels, which is now available on ArXiv!
2024.06: 🎉🎉 My project “Dynamic Self-adaptive Fusion Framework for Medical Disease Dignosis” has been selected as a Chinese National Undergraduate College Students Innovation and Entrepreneurship Program (National Key Project).

📝 Publications

Preprint

DecAlign: Hierarchical Cross-Modal Alignment for Decoupled Multimodal Representation Learning

ArXiv Preprint

Chengxuan Qian, Shuo Xing, Shawn Li, Yue Zhao, Zhengzhong Tu^†.

preprint

Re-Align: Aligning Vision Language Models via Retrieval-Augmented Direct Preference Optimization

Arxiv Preprint

Shuo Xing, Yuping Wang, Peiran Li, Ruizheng Bai, Yueqi Wang, Chengxuan Qian, Huaxiu Yao, Zhengzhong Tu^†.

Preprint

DynCIM: Dynamic Curriculum for Imbalanced Multimodal Learning

Arxiv Preprint

Chengxuan Qian, Kai Han, Jingchao Wang, Zhenlong Yuan, Chongwen Lyu, Jun Chen^†, Zhe Liu^†.

Preprint

Adaptive Label Correction Framework for Robust Medical Image Segmentation with Noisy Labels

Arxiv Preprint

Chengxuan Qian, K Han, Siqi Ma, Chongwen Lyu, Zhenlong Yuan, Jun Chen^†, Zhe Liu^†.

preview

CLIMD: A Curriculum Learning Framework for Imbalanced Multimodal Diagnosis

Under Review

Kai Han, Chongwen Lyu, Chengxuan Qian, Siqi Ma, Jun Chen^†, Zhe Liu^†,

TMI 2024

Region Uncertainty Estimation for Medical Image Segmentation with Noisy Labels

IEEE Transaction on Medical Imaging (CCF B, IF:8.9)(Major Revision)

Kai Han, Shuhui Wang, Jun Chen^†, Chengxuan Qian, Chongwen Lyu, Siqi Ma, Victor S. Sheng^†, Qingming Huang^†, Zhe Liu^†.

TCSVT 2024

Frequency Domain Unlocks New Perspectives for Medical Image Segmentation

IEEE Transactions on Circuits and Systems for Video Technology (CCF B, IF: 8.3)(Under Review)

Kai Han, Siqi Ma, Chengxuan Qian, Jun Chen^†, Chongwen Lyu, Victor S. Sheng^†, Zhe Liu^†.

TCSVT 2024

Curriculum for Region-guided Automatic Radiology Report Generation

IEEE Transactions on Circuits and Systems for Video Technology (CCF B, IF: 8.3)(Under Review)

Chongwen Lyu, Chengxuan Qian, Kai Han, Jun Chen^†, Victor S. Sheng^†, Zhe Liu^†.

MedIA 2024

LiMT: A Multi-task Liver Image Benchmark Dataset

Medical Image Analysis (IF: 10.7)(Major Revision)

Z Liu^†, K Han, S Ma, J Chen^†, …, C Qian, C Lyu, …, V S. Sheng^†.

Dataset and Benchmarking work
A multi-task medical image benchmark dataset for Segmentation, Classification and Detection of liver lesions, encompassing CT liver scans annotated for four common liver diseases.
Collaborated with researchers from Jiangsu University, Texas Tech University, and clinicians from the Affiliated Hospital of Jiangsu University.

preview

Diffusion Contrastive Learning for Image Classification

Under Review

Xincheng Zhu, Yonghan Lu, Kai Han, Chongwen Lyu, Chengxuan Qian, J Chen^†, Z Liu^†.

Note: Details of some papers above are not allowed to show since they are currently under reviewed by double-blind conference. ^† is the note for advisor.

🎖 Academical Services

Reviewer of IEEE Transactions on Circuits and Systems for Video Technology (TCSVT), IEEE Transactions on Multimedia (TMM), IEEE International Conference on Multimedia & Expo (ICME 2025) and ICCV 2025.

💬 Open-source Projects

Re-Align, a novel Direct Preference Optimization (DPO)-based alignment framework that leverages image retrieval to mitigate hallucinations in Vision Language Models. See more in the corresponding website with codes.
DecAlign, a novel cross-modal decoupling and alignment framwork for multimodal representation learning. See more in the corresponding website with codes(Will be fully released soon!).