Proposes a levels x laws taxonomy for world models in AI agents, defining L1-L3 capabilities across physical, digital, social, and scientific regimes while reviewing over 400 works to outline a roadmap for advanced agentic modeling.
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2 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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Fashion-MNIST is a new benchmark dataset of 70,000 fashion product images that serves as a direct drop-in replacement for the original MNIST dataset while being more challenging.
citing papers explorer
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Agentic World Modeling: Foundations, Capabilities, Laws, and Beyond
Proposes a levels x laws taxonomy for world models in AI agents, defining L1-L3 capabilities across physical, digital, social, and scientific regimes while reviewing over 400 works to outline a roadmap for advanced agentic modeling.
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Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms
Fashion-MNIST is a new benchmark dataset of 70,000 fashion product images that serves as a direct drop-in replacement for the original MNIST dataset while being more challenging.