CV

Education

B.S. in Electronic Information Engineering, Wuhan University, 2024
- GPA: 3.60/4.0 (87.2%)
- Third Class Scholarship of School of Electronic Information, 2021

Research Experience

Mar 2025 - May 2025: Geo-Image-Textualization
- Research Assistant, Department of Computer Science, UIUC
- Advisor: Prof. Tong Zhang
- Proposed Geo-Image-Textualization, a reinforcement learning-based framework for generating semantically aligned geometry image-caption pairs
- Constructed GeoReasoning-10K, the first dataset with full modality equivalence for geometric reasoning
- Demonstrated significant improvements in Qwen-2.5-vl performance across geometry, arithmetic, algebraic, and numeric domains
Jul 2024 - Jan 2025: Probabilistic Residual User Clustering
- Research Assistant, Department of Computer Science, Rutgers
- Advisor: Prof. Hao Wang
- Proposed PRUC, a causal Bayesian framework that clusters users and models residuals between predicted and true ratings
- Introduced a plug-and-play architecture compatible with diverse deep learning recommenders
- Demonstrated significant improvement across benchmark datasets while uncovering meaningful user clusters
May 2024 - Sep 2024: Interpretability of MLLM
- Research Assistant, Department of Computer Science, Rutgers
- Advisor: Prof. Hao Wang
- Identified strong correlations between visual inputs and token-level outputs in LLaVA
- Enhanced interpretability by uncovering underlying attention mechanisms
- Proposed adaptive pruning technique to selectively prune hierarchical attention layers
Mar 2024 - May 2024: Multimodal Needle Benchmark & Continual Learning Survey
- Research Assistant, Department of Computer Science, Rutgers
- Advisor: Prof. Hao Wang
- Evaluated performance of InstructBLIP vicuna/t5 on custom-developed benchmark
- Researched advancements in continual learning for multimodal large language models
Jun 2023 - Sep 2023: Dynamic Scene Graph Generation
- Research Assistant, Shenzhen University
- Advisors: Prof. Runhao Zeng, Chuang Gan
- Deployed Multimodal-LLM following MiniGPT4 and fine-tuned on AG datasets to generate scene graphs
- Fine-tuned class, box models in MiniGPT4’s base model by transfer learning to enhance relationship predictions
Feb 2023 - Apr 2023: Multi-Tailed Vision Transformers
- Research Assistant, Department of Computer Science, University of Sydney
- Advisor: Prof. Chang Xu
- Designed multiple tails to generate visual sequences of different lengths for Transformer encoder
- Achieved significant reduction in FLOPs with no accuracy degradation

Work Experience

Aug 2023 - Jan 2024: Visual Alignment in Industrial Settings
- Intern, Siemens, Shanghai, China
- Simulated AGV to detect cargo in Gazebo based on ROS2
- Designed visual algorithm that calculated pose and position of cargo by determining its frontal area

Skills

Programming: Proficient in Python, C++, C
Development Tools & Platforms: Experienced with ROS, Linux, and embedded systems
Research Areas:
- Multimodal Learning
- Computer Vision
- Reinforcement Learning
- Trustworthy AI
- Large Language Models

Publications

Multimodal Needle in a Haystack: Benchmarking Long-Context Capability of Multimodal Large Language Models

Hengyi Wang, Haizhou Shi, Shiwei Tan, Weiyi Qin, Wenyuan Wang, Tunyu Zhang, Akshay Nambi, Tanuja Ganu, Hao Wang. "Multimodal Needle in a Haystack: Benchmarking Long-Context Capability of Multimodal Large Language Models." NAACL 2025 Main.

Generalizable Geometric Image Caption Synthesis

Wenyuan Wang*, Yue Xin*, Rui Pan*, BingXu Meng*, Renjie Pi, Tong Zhang. "Generalizable Geometric Image Caption Synthesis." Submitted to NeurIPS Datasets and Benchmarks Track.

Probabilistic Residual User Clustering

Wenyuan Wang, Yusong Zhao, Zihao Xu, Hengyi Wang, Shreya Venugopal, Desmond Lobo, Chengzhi Mao, Qi Xu, Zhigang Hua, Yan Xie, Bo Long, Shuang Yang, Hao Wang. "Probabilistic Residual User Clustering." IJCAI2025 Workshop / Submitted to TMLR.

Multi-tailed vision transformer for efficient inference

Yunke Wang, Bo Du, Wenyuan Wang, Chang Xu. "Multi-tailed vision transformer for efficient inference." Neural Networks, 2024, 174: 106235.

Continual Learning of Large Language Models: A Comprehensive Survey

Haizhou Shi, Zihao Xu, Hengyi Wang, Weiyi Qin, Wenyuan Wang, Yibin Wang, Zifeng Wang, Sayna Ebrahimi, Hao Wang. "Continual Learning of Large Language Models: A Comprehensive Survey." ACM Computing Surveys.