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Post-training LLMs for agentic tasks can drastically reduce solution coverage, a "Sharpening Tax" that a novel Bayesian sampler can mitigate.
Robots can now navigate complex social environments with unprecedented success thanks to a new world model that anticipates both scene changes and human behavior based on potential actions.