Shize Zhang — accepted AI-conference papers

2026

UniM: A Unified Any-to-Any Interleaved Multimodal Benchmark

Yanlin Li, Minghui Guo, Kaiwen Zhang, Shize Zhang, Yiran Zhao, Haodong Li +10

CVPR 2026

In real-world multimodal applications, systems usually need to comprehend arbitrarily combined and interleaved multimodal inputs from users, while also generating outputs in any interleaved multimedia form. This capability defines the goal of any-to-any interleaved multimodal learning under a unifie

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2026

Unveiling the Cognitive Compass: Theory-of-Mind–Guided Multimodal Emotion Reasoning

Meng Luo, Bobo Li, Shanqing Xu, Shize Zhang, Qiuchan Chen, Menglu Han +5

ICLR 2026poster

Despite rapid progress in multimodal large language models (MLLMs), their capability for deep emotional understanding remains limited. We argue that genuine affective intelligence requires explicit modeling of Theory of Mind (ToM), the cognitive substrate from which emotions arise. To this end, we i…

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