MMoA: An AI-Agent framework with recurrence for Memoried Mixure-of-Agent

In three linesMMoA proposes a recurrent Mixture-of-Agents architecture with LSTM-based routing for dynamic agent selection. On AlpacaEval 2.0, MT-Bench, and Arena-Hard, MMoA achieves 58.0% win rate (vs 59.8% for MoA) while reducing computational overhead by 4.6% through selective agent activation.

Summary generated by Claude — human-verified