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Even state-of-the-art MLLMs fail to grasp intuitive visual reasoning, scoring less than 60% on tasks humans solve effortlessly at a glance.
Hierarchical Latent Prediction reduces error accumulation in language models, enabling coherent long-horizon reasoning and more efficient decoding.
