Zhengbo Jiao — accepted AI-conference papers

2026

Agentic Proposing: Enhancing Large language Model Reasoning via Compositional Skill Synthesis

Zhengbo Jiao, Shaobo Wang, Zifan Zhang, Xuan Ren, Wei Wang, Bing Zhao +2

ICML 2026poster

Advancing complex reasoning in large language models relies on high-quality, verifiable datasets, yet human annotation remains cost-prohibitive and difficult to scale. Current synthesis paradigms often face a recurring trade-off: maintaining structural validity typically restricts problem complexity…

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2026

Socratic-Geo: Synthetic Data Generation and Cross-Modal Geometric Reasoning via Multi-Agent Interaction

Zhengbo Jiao, Zifan Zhang, Shaobo Wang, Wei Wang, Bing Zhao, Hu Wei +1

CVPR 2026

Multimodal Large Language Models (MLLMs) have significantly advanced vision-language understanding. However, even state-of-the-art models struggle with geometric reasoning, revealing a critical bottleneck: the extreme scarcity of high-quality image-text pairs. Human annotation is prohibitively expen

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