Yilai Liu

About

I am Yilai Liu, currently pursuing a Master of Philosophy degree at the University of Hong Kong (HKU). I conduct my research at NICE Lab under the supervision of Prof. Hongyang Du. Before that, I received my B.Eng. degree from Beijing University of Posts and Telecommunications (BUPT).

Research

My research focuses on temporal representation modeling, with an emphasis on contextual retrieval, compression and consistency modeling in long video and mobile data.

Feel free to contact me at 2369475677@qq.com for any potential discussion, collaboration and opportunity.

Education

The University of Hong Kong
2025 - Present
The University of Hong Kong
Master of Philosophy, Department of Electrical and Computer Engineering
Beijing University of Posts and Telecommunications
2021 - 2025
Beijing University of Posts and Telecommunications
Bachelor of Engineering

Ongoing Research

***Bench - Evaluating MLLMs' capability for fine-grained temporal reasoning beyond language shortcuts.
PreCoG - Preview-guided generation-time video correction for reducing AIGC workflow costs from long single-sample inference and high rejection rates.

Selected Works

View all

Long Video Understanding & Generation

SlotMem: Character-Addressable Internal Memory for Narrative Long Video Generation
SlotMem: Character-Addressable Internal Memory for Narrative Long Video Generation
arXiv 2026
Yilai Liu, Xin Zhang, Shiyuan Zhang, and Hongyang Du
Propose SlotMem, a character-addressable internal memory framework for preserving long-range character consistency in narrative long-video generation.

Mobile Usage Behavior Modeling

MIDiff: Tackling Sparsity and Imbalance in Mobile Usage Generation via Multivariate-Imaging Diffusion
MIDiff: Tackling Sparsity and Imbalance in Mobile Usage Generation via Multivariate-Imaging Diffusion
arXiv 2026
Yilai Liu, Shiyuan Zhang, and Hongyang Du
Propose MIDiff, a multivariate-imaging diffusion framework for generating realistic and diverse mobile usage traces under sparsity and usage imbalance.
U-MASK: User-adaptive Spatio-Temporal Masking for Personalized Mobile AI Applications
U-MASK: User-adaptive Spatio-Temporal Masking for Personalized Mobile AI Applications
arXiv 2026
Shiyuan Zhang, Yilai Liu, Yuwei Du, Ruoxuan Yang, Dong In Kim, and Hongyang Du
Propose U-MASK, a uniform model for multi-tasks generazabiltity through spatio-temporal masks for contexts-retrival under sparse observations.
Poster: Enhancing Mobile Traffic Data Generation through Spatio-temporal Correlation Imaging
Poster: Enhancing Mobile Traffic Data Generation through Spatio-temporal Correlation Imaging
MobiCom Poster 2025
Yilai Liu, Shiyuan Zhang, Hongyang Du
Address the challenge of users' daily mobile usage modeling under usage sparsity by correlation imaging for data augmentation.

Competitions & Awards

ISPRS TC I Contest on Remote Sensing - Rank 2/43 2024
China International College Students' Innovation Competition - National Second Prize 2024
Chinese Mathematics Competitions for College Students - National Second Prize 2022