A lightweight projection layer trained to align frozen SpectralGPT multispectral features with LLaMA-3 text embeddings markedly improves EuroSAT classification and enables multispectral scene description.
First principles residual resistivity using locally self-consistent multiple scattering method
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abstract
The locally self-consistent multiple scattering (LSMS) method can perform efficient first-principles calculations of systems with large number of atoms. In this work, we combine the Kubo-Greenwood equation with LSMS, enabling us to calculate first-principles residual resistivity of large systems. This has been implemented in the open-source code lsms. We apply this method to selected pure elements and binary random alloys. The results compare well with experiment, and with values obtained from a first-principles effective medium technique (KKR-CPA). We discuss future applications of this method to complex systems where other methods are not applicable.
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A Vision-Language Framework for Multispectral Scene Representation Using Language-Grounded Features
A lightweight projection layer trained to align frozen SpectralGPT multispectral features with LLaMA-3 text embeddings markedly improves EuroSAT classification and enables multispectral scene description.