I am a first-year M.S. student at Peking University, advised by Prof. Li Yuan. I have also been fortunate to work closely with Prof. Lei Feng and Prof. Ziwei Liu.

My core research focuses on visual representations and language priors. Vision directly depicts the physical appearance of the "real world"; while language, as the refinement and abstraction of visual information, constructs the knowledge landscape of the "human world." I firmly believe that bridging the gap between the language modality, which carries "human world" prior knowledge, and the visual modality, which directly reflects the "real world," is a crucial step towards achieving general artificial intelligence. This not only involves finding effective mapping paths between modalities but also concerns how to leverage their respective strengths to build a unified framework collaboratively.

Currently, I am dedicated to researching model architectures and building multimodal intelligence.

🤝 I am eager to discuss potential collaborations and am actively seeking industry internship opportunities in multimodal models. Please feel free to contact me via email if you are interested.

• 
  Peking University M.S. in Computer Science, School of Electronic and Computer Engineering
  2026 – 2029
• 
  Chongqing University B.Eng. in Computer Science, Hongshen Stand-Out Class
  2022 – 2026

• 
  NTU LMMs-Lab Visiting Student / Research Intern
  Mar 2026 – Nov 2026
• 
  ByteDance Seed-Vision Research Intern
  Sep 2025 – Mar 2026

Full paper list can be found on Google Scholar.  * Equal Contribution   † Project Lead

• 
  ICML 2026

  WISE: A World Knowledge-Informed Semantic Evaluation for Text-to-Image Generation

  Yuwei Niu*, Munan Ning*, Mengren Zheng, Weiyang Jin, Bin Lin, Peng Jin, Jiaqi Liao, Chaoran Feng, Kunpeng Ning, Bin Zhu, Li Yuan†.

  Paper Code
• 
  EMNLP 2026

  Does Understanding Inform Generation in Unified Multimodal Models? From Analysis to Path Forward

  Yuwei Niu*, Weiyang Jin*, Jiaqi Liao, Chaoran Feng, Peng Jin, Bin Lin, Zongjian Li, Bin Zhu, Weihao Yu, Li Yuan†.

  Paper Code
• 
  AAAI 2026

  Look-Back: Implicit Visual Re-focusing in MLLM Reasoning

  Shuo Yang*, Yuwei Niu*, Yuyang Liu†, Yang Ye, Bin Lin, Li Yuan†.

  Paper Code
• 
  ECCV 2026

  SRUM: Fine-Grained Self-Rewarding for Unified Multimodal Models

  Weiyang Jin*, Yuwei Niu*, Jiaqi Liao, Chengqi Duan, Aoxue Li, Shenghua Gao, Xihui Liu†.

  Paper Code
• 
  ICCV 2025

  LangBridge: Interpreting Image as a Combination of Language Embeddings

  Jiaqi Liao*, Yuwei Niu*, Fanqing Meng*, Hao Li, Changyao Tian, Yinuo Du, Yuwen Xiong, Dianqi Li, Xizhou Zhu, Li Yuan, Jifeng Dai†, Yu Cheng†.

  Paper Code
• 
  ICML 2025

  Test-Time Multimodal Backdoor Detection by Contrastive Prompting

  Yuwei Niu*, Shuo He*, Qi Wei, Zongyu Wu, Feng Liu, Lei Feng†.

  Paper Code

• 
  Tech Report

  SenseNova-U Series

  SenseNova-U Team

  • SenseNova-U1.5: Towards Native Unified Visual Intelligence
  • SenseNova-U1: Unifying Multimodal Understanding and Generation with NEO-unify Architecture

  Code 6.9k
• 
  Tech Report

  From Pixels to Words -- Towards Native One-Vision Models at Scale

  NEO-ov Team

  Paper Code 925
• 
  Tech Report

  UniWorld Series

  UniWorld Team

  • UniWorld: High-Resolution Semantic Encoders for Unified Visual Understanding and Generation
  • UniWorld-V2: Reinforce Image Editing with Diffusion Negative-aware Finetuning and MLLM Implicit Feedback

  Code 894

• Purshow's Notes Bilingual (CN/EN) research notes on Attention, MoE, Muon, On-Policy Distillation, Vision Encoders, Encoder-Free Models, Video VAEs, World Action Models, YOCO, Sparse Vocab Embeddings, and Beyond Residual Connection.
• Why Removing the Vision Encoder Can Be Better — From an Infra Perspective
• When Vision Is Pushed to the Roadside
• The (Possible) Future of Multimodal Understanding: From Describing the World to Entering the World

I occasionally write blogs to share my thoughts. Chinese readers can find the full archive on my RedNote.

Beyond science, I am deeply passionate about literature, poetry, anime, films, music, and all forms of art that embody human creativity. I firmly believe these are the reasons for our existence. Currently, I am deeply captivated by the literature of Dostoevsky and Tolstoy, and R&B music (such as Prince, Stevie Wonder, D'Angelo, David Tao, and Khalil Fong).

I believe good ideas and meaningful progress often come from open discussion and thoughtful disagreement. If you have comments on my work, different perspectives, or new ideas you would like to share, I would be very happy to hear from you.

I have been fortunate to meet many friends and mentors who have helped me along the way. I am also always happy to chat and offer whatever help I can to others.

If you have questions about my research, or if you have tried to reach me through GitHub issues but have not received a response, please feel free to email me directly.

My preferred email: niuyuwei04@gmail.com