Final-year PhD at MMLab@NTU, advised by Prof. Ziwei Liu.
I build and evaluate multimodal large language models, with a focus on post-training and benchmarking.
Current Interests
Information-dense Video Reasoning: Building models that identify salient details, connect dispersed evidence, and infer causal structure in complex visual narratives.
Harness-centric LLM Systems: Designing harnesses that structure memory for effective in-context comprehension and encode success criteria as robust executable checks.
Benchmarking Model–Human Gaps: Developing diagnostic benchmarks that reveal systematic differences between models and humans, and suggest better optimization targets.
Kairui Hu, Penghao Wu, Fanyi Pu, Wang Xiao, Xiang Yue, Bo Li, Yuanhan Zhang, Ziwei Liu
A multi-discipline video benchmark for knowledge acquisition — adopted by Gemini-3 as part of their evaluation suite.
Yuanhan Zhang*, Yunice Chew*, Yuhao Dong, Aria Leo, Bo Hu, Ziwei Liu
A video reasoning benchmark that eliminates key-frame sampling bias — exposes a 48-point gap between GPT-4o (36.6%) and humans (84.3%).
Yuanhan Zhang, Jinming Wu, Wei Li, Bo Li, Zejun Ma, Ziwei Liu, Chunyuan Li
An open video LMM built entirely on synthetic data — 1.2M+ HuggingFace downloads.
Bo Li, Yuanhan Zhang, Dong Guo, Renrui Zhang, Feng Li, Hao Zhang, Kaichen Zhang, Yanwei Li, Ziwei Liu, Chunyuan Li
One model for image, multi-image, and video — SOTA across all three.
