Author

Yi-Ning Hong

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Preprint Sep 2026

T$^2$Mem: Learning Test-Time Memory for Robotics

Memory-dependent robotic manipulation requires policies to use information that is no longer available in the current observation. Retaining history alone is insufficient: memory must preserve information that supports future actions. One challenge is whether a memory-free foundation model can learn to retain and use h...

Yi-Ze Liu, Huang Huang, Yi-Ning Hong et al. · 0 citations

#artificial intelligence Preprint Sep 2026

UniEvo-VL: An On-policy Self-Distillation Training Recipe for Multimodal Model Self-improvement

Modern multimodal models bring generation and understanding into a single unified system, which enables them to provide and learn from their own feedback. Motivated by this unified capacity, we introduce UniEvo-VL, a self-evolving framework for multimodal models to learn from this constructive self-correction feedback...

Fang Wu, Dan-Lei Xing, Yan-Jie Huang et al. · 0 citations

#artificial intelligence Preprint Sep 2026

MindTopo: Can Foundation Models Reason in Topological Space?

Spatial reasoning depends not only on metric properties such as distance, angle, and shape, but also on topological relations that remain invariant under continuous deformation. Cognitive science identifies these relations as foundational to spatial understanding, yet foundation-model evaluations largely focus on metri...

Yun-Fei Ge, An-Bang Liu, Qineng Wang et al. · 0 citations