Zhengzhao Feng — accepted AI-conference papers

2026

ProactiveMobile: A Comprehensive Benchmark for Boosting Proactive Intelligence On Mobile Devices

Dezhi Kong, Zhengzhao Feng, Qiliang Liang, Hao Wang, Haofei Sun, Changpeng Yang +9

CVPR 2026

Multimodal large language models (MLLMs) have made significant progress in mobile agent development, yet their capabilities are predominantly confined to a reactive paradigm, where they merely execute explicit user commands. The emerging paradigm of proactive intelligence, where agents autonomously

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2025

Efficient Dynamic Graphs Learning with Refined Batch Parallel Training

Zhengzhao Feng, Rui Wang, Longjiao Zhang, Tongya Zheng, Ziqi Huang, Mingli Song

IJCAI 2025

Memory-based temporal graph neural networks (MTGNN) use node memory to store historical information, enabling efficient processing of large dynamic graphs through batch parallel training, with larger batch sizes leading to increased training efficiency. However, this approach overlooks the interdepe

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