Zongmeng Wang — accepted AI-conference papers

2026

Dual-level Adaptation for Multi-Object Tracking: Building Test-Time Calibration from Experience and Intuition

Wen Guo, Pengfei Zhao, Zongmeng Wang, Yufan Hu, Junyu Gao

CVPR 2026

Multiple Object Tracking (MOT) has long been a fundamental task in computer vision, with broad applications in various real-world scenarios. However, due to distribution shifts in appearance, motion pattern, and catagory between the training and testing data, model performance degrades considerably

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2026

SC$^{2}$-WM: A Self-Correcting World Model with Closed-Loop Feedback for Vision-and-Language Navigation in Continuous Environments

Xuan Yao, Yuze Zhu, JUNYU GAO, Zongmeng Wang, Changsheng Xu

ICML 2026poster

Vision-and-Language Navigation in Continuous Environments (VLN-CE) requires agents to make fine-grained navigation decisions under partial observability. However, most existing methods rely on open-loop execution, lacking mechanisms to detect and correct internal state drift during inference. We pro…

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