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From Words to Routes: Applying Large Language Models to Vehicle Routing
The success of LLMs in these tasks leads us to wonder: What is the ability of LLMs to solve vehicle routing problems (VRPs) with natural language task descriptions?
Decision-Oriented Learning with Differentiable Submodular Maximization for Vehicle Routing Problem
We study the problem of learning a function that maps context observations (input) to parameters of a submodular function (output).
Dimensionality Reduction of Hyperspectral Imagery Based on Spatial-spectral Manifold Learning
However, a major challenge of GE is how to choose proper neighbors for graph construction and explore the spatial information of HSI data.
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