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Found 3 papers, 3 papers with code
LLMs learn governing principles of dynamical systems, revealing an in-context neural scaling law
Pretrained large language models (LLMs) are surprisingly effective at performing zero-shot tasks, including time-series forecasting.
Coneheads: Hierarchy Aware Attention
These networks rely heavily on the dot product attention operator, which computes the similarity between two points by taking their inner product.
Shadow Cones: A Generalized Framework for Partial Order Embeddings
Specifically, we model partial orders as subset relations between shadows formed by a light source and opaque objects in hyperbolic space.
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