Update README.md

README.md

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 ## Model Overview
 
-Nemotron-Flash is a new hybrid small language model family designed around real-world latency rather than parameter count. It features latency-optimal depth–width ratios, hybrid operators discovered through evolutionary search, and training-time weight normalization. 
+Nemotron-Flash is a new hybrid small language model family designed around real-world latency rather than parameter count. It features latency-optimal depth–width ratios, hybrid operators discovered through evolutionary search, and training-time weight normalization. See our <a href="https://arxiv.org/pdf/2511.18890">NeurIPS 2025 paper</a> for more technical details.
 
 The models achieve SOTA accuracy in math, coding, and commonsense reasoning at the 1B and 3B scales, while delivering decent small-batch latency and large-batch throughput. For example, Nemotron-Flash-1B achieves +5.5% accuracy, 1.9× lower latency, and 45.6× higher throughput compared with Qwen3-0.6B; and Nemotron-Flash-3B achieves +2% / +5.5% accuracy over Qwen2.5-3B / Qwen3-1.7B with 1.3× / 1.7× lower latency and 6.4× / 18.7× higher throughput, respectively.