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Localized latent reasoning can slash inference latency while maintaining competitive accuracy, challenging the need for larger models or lengthy reasoning chains.
Even the best vision-language models struggle to reliably set fine-grained GUI states, achieving only 33% accuracy on a new benchmark, but targeted visual hints suggest a clear path to improvement.
