Zekun Wang

Hi, my name is Zekun Wang (汪泽堃 in Chinese). I am currently a final year Ph.D. student from SCIR @ Harbin Institute of Technology. Fortunately, I am advised by Prof. Ming Liu and Prof. Bing Qin. I expect to graduate in 2025. Prior to this, I received my bachelar degree from Harbin Institute of Technology in 2019.

My research interests have evolved to focus on developing:

• Model/Data-Efficiency & Acceleration: Efficient architecture for XFMRs or hybrid ones; Pruning, distillation, quantization etc. to reduce model size and speedup inference; Efficient training LLMs/MLLMs with a small cost (time or data).

• Multi-modal Models and Applications: Large multi-modal models (comprehensive, generation, or unify the both), which support diverse tasks and can be applied as agents in digital or embodied environments.

I am particularly interested in exploring the intrinsic relationship between model (efficient) architecture and its performance, as well as how to unlock its potential in real-world scenarios.

News:

• 🔥🔥 Two papers have been accepted by ICLR’25. See you in Singapore!
• 🔥 One paper has been accepted by COLING’25. See you in Abu Dhabi, UAE!
• 🚀 Qwen2.5 Technical Report is released.

Selected Publications:

Full publications can be found in [Semantic Scholar] [Google Scholar] (* denotes equal contributions.)

• Improved Diffusion-based Generative Model with Better Adversarial Robustness
  Zekun Wang*, Mingyang Yi*, Shuchen Xue, Zhenguo Li, Ming Liu, Bing Qin, Zhi-Ming Ma
  ICLR 2025
  [pdf]
  

• AgentTrek: Agent Trajectory Synthesis via Guiding Replay with Web Tutorials
  Yiheng Xu, Dunjie Lu, Zhennan Shen, Junli Wang, Zekun Wang, Yuchen Mao, Caiming Xiong, Tao Yu
  ICLR 2025 Spotlight (Top 5%)
  [pdf] [project]
  

• CFSP: An Efficient Structured Pruning Framework for LLMs with Coarse-to-Fine Activation Information
  Yuxin Wang*, Minghua Ma*, Zekun Wang*, Jingchang Chen, Huiming Fan, Liping Shan, Qing Yang, Dongliang Xu, Ming Liu, Bing Qin.
  COLING 2025
  [pdf] [project]
  

• Demons in the Detail: On Implementing Load Balancing Loss for Training Specialized Mixture-of Expert Models
  Zihan Qiu, Zeyu Huang, Bo Zheng, Kaiyue Wen, Zekun Wang, Rui Men, Ivan Titov, Dayiheng Liu, Jingren Zhou, Junyang Lin
  Preprint 2025
  [pdf]
  

• Aguvis: Unified Pure Vision Agents for Autonomous GUI Interaction
  Yiheng Xu*, Zekun Wang*, Junli Wang*, Dunjie Lu, Tianbao Xie, Amrita Saha, Doyen Sahoo, Tao Yu, Caiming Xiong
  Preprint 2024
  [pdf] [project]
  

• Qwen2.5 Technical Report
  Qwen Team
  Technical Report
  [pdf] [project] [collection]
  

• Divide-and-Conquer Meets Consensus: Unleashing the Power of Functions in Code Generation
  Jingchang Chen, Hongxuan Tang, Zheng Chu, Qianglong Chen, Zekun Wang, Ming Liu, Bing Qin
  NeurIPS 2024 Oral
  [pdf]
  

• SmartTrim: Adaptive Tokens and Attention Pruning for Efficient Vision-Language Models
  Zekun Wang*, Jingchang Chen*, Wangchunshu Zhou, Haichao Zhu, Jiafeng Liang, Liping Shan, Ming Liu, Dongliang Xu, Qing Yang, Bing Qin
  COLING 2024 Oral
  [pdf]
  

• Distilled Dual-Encoder Model for Vision-Language Understanding
  Zekun Wang, Wenhui Wang, Haichao Zhu, Ming Liu, Bing Qin, Furu Wei
  EMNLP 2022 [pdf] [project]

• Less Is More: Domain Adaptation with Lottery Ticket for Reading Comprehension
  Haichao Zhu, Zekun Wang, Heng Zhang, Ming Liu, Sendong Zhao, Bing Qin
  Findings of EMNLP 2021
  [pdf]
  

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