An LLM-based multi-agent system (FORMA) verifies DESI spectral classifications with 95.5% agreement to expert adjudication by reconstructing expert reasoning into an auditable workflow.
https://arxiv.org/abs/2511.08970
2 Pith papers cite this work. Polarity classification is still indexing.
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2026 2representative citing papers
Two-stage LLM framework infers stellar parameters and ~20 elemental abundances from spectra, showing performance gains with increasing data volume.
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Executable verification through formalized expert reasoning in astronomical spectroscopy
An LLM-based multi-agent system (FORMA) verifies DESI spectral classifications with 95.5% agreement to expert adjudication by reconstructing expert reasoning into an auditable workflow.
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Spectra as Language: Large Language Models for Scalable Stellar Parameter and Abundance Inference
Two-stage LLM framework infers stellar parameters and ~20 elemental abundances from spectra, showing performance gains with increasing data volume.