Flow matching on time series targets a closed-form nonparametric velocity field that is a similarity-weighted mixture of observed transition velocities, making neural models approximations to an ideal memory-augmented dynamical system sampler.
On estimating regression.Theory of Probability & Its Applications, 9(1):141–142
3 Pith papers cite this work. Polarity classification is still indexing.
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AI editing of human texts introduces directional biases that amplify through social networks to steer collective opinions, demonstrated empirically and via an analytical model with a real-world audit of Grok on X.
Cubit replaces Transformer's attention with a closed-form Kernel Ridge Regression token mixer and reports larger gains as training sequence length increases.
citing papers explorer
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Is Flow Matching Just Trajectory Replay for Sequential Data?
Flow matching on time series targets a closed-form nonparametric velocity field that is a similarity-weighted mixture of observed transition velocities, making neural models approximations to an ideal memory-augmented dynamical system sampler.
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AI-Mediated Communication Can Steer Collective Opinion
AI editing of human texts introduces directional biases that amplify through social networks to steer collective opinions, demonstrated empirically and via an analytical model with a real-world audit of Grok on X.
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Cubit: Token Mixer with Kernel Ridge Regression
Cubit replaces Transformer's attention with a closed-form Kernel Ridge Regression token mixer and reports larger gains as training sequence length increases.