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Black-Mamba introduces a test-time adaptive forecasting architecture that uses accumulated surprisal to selectively update memory only upon evidence of distribution drift, achieving efficient adaptation on non-stationary time series.
FLYNN is a recurrent neural network derived from the fruit fly brain connectome for vision-based robot navigation. It achieves comparable performance to handcrafted networks while showing superior robustness to out-of-distribution data and sensory loss.