QUEST: A robust attention formulation using query-modulated spherical attention

1. 1Identify the limitations of standard attention formulation in Transformer models
2. 2Analyze the role of query and key vector norms in causing training instabilities
3. 3Implement query-modulated spherical attention to improve training stability
4. 4Evaluate the performance of QUEST in various deep learning tasks

ML researchers and engineers working on Transformer models can benefit from this research to improve their model's performance and stability, and software engineers can apply this knowledge to develop more robust AI systems

💡 Query-modulated spherical attention can improve training stability in Transformer models by reducing the impact of arbitrarily increasing query and key vector norms

🤖 QUEST: A new attention formulation for robust Transformer training! 🚀