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Even advanced LLMs struggle to prevent privacy breaches in multi-user settings, exposing critical data spillage risks that current benchmarks overlook.
Conditioning LLMs on human privacy judgments leads to a remarkable increase in alignment with user expectations, showcasing a new standard for agent training.
Forcing VLMs to "think" visually with panoramic renderings, rather than relying on language alone, unlocks surprisingly robust spatial reasoning.
