generated-article-tucker-attention
Introduction The relentless pursuit of more efficient large language models has led to continuous innovation in attention mechanism design. As transformer architectures scale to unprecedented sizes, researchers face critical challenges in managing computational resources while maintaining model performance. The memory footprint of self-attention mechanisms, in particular, has become a significant