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Landmark finding that showed brains of kids with ADHD mature later was actually a mirage in the data, new research finds
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Romanian investigation finds Russia was behind drone strike after Putin’s denial
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Lawyers fighting SJSU over volleyball scandal respond to federal Title IX probe findings
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SJSU volleyball scandal probe finds team allegedly recruited male for advantage without telling female players
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'Don't scare the cat!' Engineers find smarter way to measure quantum systems
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Octopuses use mirrors to find food they cannot see
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Wetlands loss has increased residential flood insurance claim payments by $10 billion across the US, study finds
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This blood-feeding fly sacrifices its sight after finding a host
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Attention-based optimizer for symmetry finding
arXiv:2605.30429v1 Announce Type: cross Abstract: Finding symmetries is crucial for understanding physical models. In this work, we present an optimization framework that searches Pauli symmetries of Hamiltonians, merging the fields of machine learning with automated symmetry finding. Built on a Set-Transformer architecture, our framework uses self-attention to encode the pairwise and higher-order correlations among the Pauli-Strings.