Nota AI Advances MoE Quantization With Two EMNLP 2026 Papers
As large language models move toward trillion-parameter scale, reducing the cost of running them is becoming almost as important as improving their accuracy. Nota AI is targeting that problem with two research papers accepted at EMNLP 2026, including one selected for the conference’s Main Conference. Both studies focus on a difficult optimization problem in Mixture-of-Experts…
