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ToolArtist achieves unprecedented synergy in image generation by unifying reasoning and tool use under a single agent policy, outperforming conventional methods.
Shifting the focus from static state transitions to dynamic, agent-centric feedback could revolutionize how we train and evolve intelligent agents.
LaMem-VLA seamlessly integrates historical experience into VLA reasoning, enabling robots to perform complex tasks with improved contextual awareness.
DOPD reveals that intelligently routing supervision based on advantage gaps can significantly enhance capability transfer in distillation, outperforming conventional methods.
Language models are increasingly doing their real work in the "invisible" latent space, not the tokens we see.
