Multi-Particle Dynamical Systems Modeling Transformers

Key Points

• The multi-particle dynamical system formulation models self-attention in transformers, enhancing understanding.
• Analysis reveals the systematic behavior of the system's convergence towards clusters through this formulation.
• The relation with the Kuramoto oscillator provides insights into synchronization dynamics in deep learning models.
• Literature review synthesizes current understanding and applications of dynamical systems in neural networks.

Abstract