Yuchi Wang

Yuchi Wang

Master Student of Artificial Intelligence

Lanco Lab

Peking University

Biography

Hi! I’m a final year master’s student at the AAIS (Academy for Advanced Interdisciplinary Studies), Peking University. Currently, I am a member of Lanco Lab, lead by Prof. Xu Sun. Previously, I earned my Bachelor’s degree from the School of Data Science, Fudan University.

My research interests encompass (1) Multimodal learning, including visual understanding, text-guided visual generation (e.g., image/video generation or editing, talking face generation), etc (2) Generative Models such as diffusion models and VAEs (3) LLMs (especially multimodal large language models) and their applications like embodied AI.

I’m currently seeking a potential PhD position. Feel free to reach out if you are interested!

Interests
  • Multimodal learning
  • Generativa AI (AIGC)
  • Large language models
  • Diffusion models
Education

  • Master in Data Science, Peking University, 2025 (Expected)

    Lanco Lab; Advisor: Xu Sun; AAIS

  • BSc in Data Science, Fudan University, 2022

    School of Data Science; GPA Rank: 3/85

News

  • [2024.05] One paper accepted by ACL 2024 (Findings)
  • [2024.03] One paper accepted by NAACL 2024
  • [2024.01] One paper accepted by ICLR 2024
  • [2023.10] We release GAIA demo!
  • [2023.10] One paper accepted by FMDM@NeurIPS 2023
  • [2023.05] Starting internship at MSRA ML Group
  • [2022.09] Joining in Lanco Lab, Peking University

All Publications

[ArXiv] Rethinking Semantic Parsing for Large Language Models: Enhancing LLM Performance with Semantic Hints
we propose SENSE, a novel prompting approach that embeds semantic hints within the prompt. Experiments show that SENSE consistently improves LLMs’ performance across various tasks, highlighting the potential of integrating semantic information to improve LLM capabilities.
Kaikai An, Shuzheng Si, Helan Hu, Haozhe Zhao, Yuchi Wang, Qingyan Guo, Baobao Chang
Cite
[ArXiv] Make Your Actor Talk: Generalizable and High-Fidelity Lip Sync with Motion and Appearance Disentanglement
We present MyTalk, aiming to edit the lip movements in talking video according to the given speech while preserving the personal identity and visual details.
Runyi Yu, Tianyu He, Ailing Zeng, Yuchi Wang, Junliang Guo, Xu Tan, Chang Liu, Jie Chen, Jiang Bian
PDF Cite Demo Page
[ArXiv] InstructAvatar: Text-Guided Emotion and Motion Control for Avatar Generation
We present InstructAvatar, a novel text-guided approach for generating emotionally expressive 2D avatars, offering fine-grained control, improved interactivity and generalizability to the resulting video.
Yuchi Wang, Junliang Guo, Jianhong Bai, Runyi Yu, Tianyu He, Xu Tan, Xu Sun, Jiang Bian
PDF Cite Code Demo Page
[ArXiv] InstructAvatar: Text-Guided Emotion and Motion Control for Avatar Generation
[NAACL 2024] LaDiC: Are Diffusion Models Really Inferior to Autoregressive Counterparts for Image-to-Text Generation?
We explore the previously untapped advantages of diffusion models over autoregressive (AR) methods in image-to-text generation. Through meticulous design of a latent-based diffusion model tailored for captioning, we achieve comparable performance with some strong AR baselines.
Yuchi Wang, Shuhuai Ren, Rundong Gao, Linli Yao, Qingyan Guo, Kaikai An, Jianhong Bai, Xu Sun
PDF Cite Code
[NAACL 2024] LaDiC: Are Diffusion Models Really Inferior to Autoregressive Counterparts for Image-to-Text Generation?
[ArXiv] UniEdit: A Unified Tuning-Free Framework for Video Motion and Appearance Editing
We present UniEdit, a tuning-free framework that supports both video motion and appearance editing by harnessing the power of a pre-trained text-to-video generator within an inversion-then-generation framework.
Jianhong Bai, Tianyu He, Yuchi Wang, Junliang Guo, Haoji Hu, Zuozhu Liu, Jiang Bian
PDF Cite Code Demo Page
See all publications

Work Experience

 
 
 
 
 
Microsoft Research Asia (MSRA)
Research Intern
Microsoft Research Asia (MSRA)
May 2023 – Present Beijing, China
  • Excited to join the ML group, advised by Junliang Guo and Xu Tan.
  • During my internship up to now, I have primarily focused on generative learning, including talking avatar generation, video generation/editing.

Academic Service

Teaching Assistant

I am currently serving as a teaching assistant for the course Large Language Model in Decision Intelligence (PKU Class 2024 Spring). This course is tailored for undergraduates, aiming to provide them with a foundational understanding of large language models and effective strategies for their utilization.