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SPARGen achieves competitive performance across diverse spatial tasks by unifying perception and reasoning into a single generative framework, challenging the need for separate architectures.
A single unified model can outperform specialized systems across various computer vision tasks, all without the need for custom architectures.
LLMs struggle with multi-turn conversations not because they lack information, but because they get anchored on unsupported assumptions made early in the conversation.
