Repulsor: Speeding Up Generative Models with Memory

The Repulsor paper introduces a novel contrastive memory bank to accelerate generative modeling. The approach likely offers significant performance improvements by efficiently storing and retrieving relevant information during generation.

• •Repulsor utilizes a contrastive memory bank.
• •The core aim is to improve the speed of generative models.
• •This could lead to more efficient and faster AI applications.