Enhancing Transformer Architectures with Non-Sequential Layer Connectivity for Improved Creativity and Problem Solving
Abstract Traditional transformer architectures utilize sequential layer connectivity, limiting the complexity of potential interactions. This paper proposes a novel modification by introducing randomized, non-sequential layer connectivity aimed at enhancing the model's creativity, learning capabilities, and problem-solving efficiency. Additionally, we explore integrating external model feedback to optimize these new connections dynamically. This proposal outlines the architectural change...
Enhancing Transformer Architectures with Non-Sequential Layer Connectivity for Improved Creativity and Problem Solving
Abstract Traditional transformer architectures utilize sequential layer connectivity, limiting the complexity of potential interactions. This paper proposes a novel modification by introducing randomized, non-sequential layer connectivity aimed at enhancing the model's creativity, learning capabilities, and problem-solving efficiency. Additionally, we explore integrating external model feedback to optimize these new connections dynamically. This proposal outlines the architectural change...
