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Beijing, China

Ye Tian

Deep Learning · Diffusion Models · Multimodal LLM

I’m Ye Tian (田野), an incoming Ph.D. student at School of Intelligence Science and Technology, Peking University, advised by Prof. Yunhai Tong. My academic journey at Peking University also includes completing my bachelor’s and master’s degrees in Computer Science at the School of Computer Science and Electronic Engineering, where I had the privilege of collaborating closely with Prof. Bin Cui and Ph.D. Ling Yang.

My research interests mainly focus on AI-Generated Visual Content, multi-modal LLM, and unified models. My current focus is dedicated to exploring and advancing diffusion-based language models, and we aim to develop state-of-the-art diffusion models for unified understanding and generation.

I’m always open to academic or industry collaborations; please feel free to reach out at tyfeld@gmail.com.

news

May 21, 2025 MMaDA is released, and I serve as the core code contributor. We built a novel unified multimodal understanding and generation model, purely with a discrete diffusion backbone.

selected publications

  1. arXiv 2025
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    MMaDA: Multimodal Large Diffusion Language Models
    Ling Yang*, Ye Tian*, Bowen Li, and 4 more authors
    arXiv preprint arXiv:2505.15809, 2025
  2. NeurIPS 2024
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    Videotetris: Towards compositional text-to-video generation
    Ye Tian, Ling Yang, Haotian Yang, and 8 more authors
    Advances in Neural Information Processing Systems, 2024