<ul><li>Researchers have proposed a synthetic benchmarking framework to evaluate the effectiveness of different sequence models in capturing various temporal structures.</li><li>The framework involves generating synthetic targets characterized by memory functions and parameters that determine the strength of temporal dependence.</li><li>Experiments on different sequence modeling architectures using this framework confirm existing theoretical insights and uncover new findings.</li><li>The results show that using controllable targets with clear structures is crucial for evaluating and advancing theoretical understanding in sequence modeling.</li></ul>

Numerical Investigation of Sequence Modeling Theory using Controllable Memory Functions

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