Zhili Liu's Homepage

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About Me

I am currently a Ph.D. candidate in CSE department of Hong Kong University of Science and Technology (HKUST), supervised by Prof. James Kwok. I hold a Master's degree in Computer Science from CUHK (2019) and a Bachelor's degree in Software Engineering from Tongji University (2018).

I'm currently seeking job opportunities and would welcome you to connect with me via email.

My current research projects include:

Mixture of cluster-conditional experts: MoCLE, MoCE, SDR
Model Reasoning & Safety: Atomthink, MoTE, Geom-Erasing, ECSO
Omni-modal: EMOVA

News

[2025.05] MoTE is accepted by ACL 2025!
[2025.02] EMOVA is accepted by CVPR 2025!
[2024.09] We announce EMOVA, a novel end-to-end omni-modal model (i.e., w/o ASR or TTS) with SoTA vision-language and speech abilities, further supporting emotional dialogue. Stay tuned for more details after ECCV!
[2024.07] Implicit Concept Dataset is release on HuggingFace. Welcome to try!
[2024.07] Two papers Geom-Erasing and ECSO are accepted by ECCV 2024! See you in Milano, Italy!
[2023.12] Our MoCLE is reported by Liangziwei!
[2023.05] MoCE is reported by Noah's Ark Lab!
[2023.01] MoCE is accepted by ICLR 2023 as Spotlight Top25%! See you in Kigali, Rwanda!
[2022.05] SDR is accepted by AAAI 2022!

Selected Publications

Full publication list on Google Scholar. (* denotes equal contribution)

Mixture of Cluster-conditional Experts

Mixture of Cluster-conditional LoRA Experts for Vision-language Instruction Tuning

Yunhao Gou*, Zhili Liu*, Kai Chen*, Lanqing Hong, Hang Xu, Aoxue Li, Dit-Yan Yeung, James Kwok, Yu Zhang.

First MLLM with MoE for instruction customization and generalization!

Arxiv preprint, 2023.

[PDF] [Project page] [Wechat Post] [Talk]

Task-customized Masked Autoencoder via Mixture of Cluster-conditional Experts

Zhili Liu*, Kai Chen*, Jianhua Han, Lanqing HONG, Hang Xu, Zhenguo Li, James Kwok.

International Conference on Learning Representations (ICLR), 2023 (Spotlight Top25%).

[PDF][Wechat Post]

Task-Customized Self-Supervised Pre-training with Scalable Dynamic Routing.

Zhili Liu, Jianhua Han, Kai Chen, Lanqing Hong, Hang Xu, Chunjing Xu, Zhenguo Li.

AAAI Conference on Artificial Intelligence (AAAI), 2022.

[PDF]

Model Reasoning & Safety

AtomThink: A Slow Thinking Framework for Multimodal Mathematical Reasoning

Kun Xiang*, Zhili Liu*, Zihao Jiang*, Yunshuang Nie, Runhui Huang, Haoxiang Fan, Hanhui Li, Weiran Huang, Yihan Zeng, Jianhua Han, Lanqing Hong, Hang Xu, Xiaodan Liang

First o1-like slow think framework for MLLM!

Arxiv preprint, 2024.

[PDF][Github]