2 papers
cs.AI2026
Learning to Learn from Multimodal Experience
Xingyu Sui, Weixiang Zhao, Yongxin Tang +4
Experience-driven learning has emerged as a promising paradigm for enabling agents to improve from interaction trajectories by accumulating and reusing past experience. However, ex…
cs.AI2025
AllSpark: A Multimodal Spatio-Temporal General Intelligence Model with Ten Modalities via Language as a Reference Framework
Run Shao, Cheng Yang, Qiujun Li +8
Leveraging multimodal data is an inherent requirement for comprehending geographic objects. However, due to the high heterogeneity in structure and semantics among various spatio-t…