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cs.AI2026
Learning Intrinsic Dynamics in Latent World Models
Jiamin Shi, Yuanhong Zhang, Zhiyang Liu +2
Learning intrinsic dynamics---the relationship between actions and their consequences---is essential for world models. However, visual variations unrelated to the underlying contro…
cs.AI2026
Improving Auto-Design of Neural PDE Solvers with a Domain-Specific Language
Shengxin Kong, Liwen Xu, Jingwen Fu
Neural PDE solver auto-design is fundamentally a search-space representation problem. In the space of unrestricted Python programs, valid solvers form an extremely sparse subset: m…
cs.AI2026
Shaping Schema via Language Representation as the Next Frontier for LLM Intelligence Expanding
Zhiqin Yang, Yuhan Liu, Jingwen Fu +4
Although natural language is the default medium for Large Language Models (LLMs), its limited expressive capacity creates a profound bottleneck for complex problem-solving. While r…