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Language agents can achieve superior sample efficiency and performance by jointly learning to act and forecast multi-step action sequences within a single policy backbone.
Selective orbital filtering in a halogen monolayer circumvents the complex $d$-orbital interference of traditional kagome materials, unlocking the first experimental realization of an intrinsically topological $p_{x,y}$ kagome electronic structure.
Achieving a staggering 54.67× speedup in text-to-video-audio generation without sacrificing quality could revolutionize real-time multimedia applications.