AdaFuse: Adaptive Ensemble Decoding with Test-Time Scaling for LLMs

This paper proposes AdaFuse, an adaptive ensemble decoding method with test-time scaling for large language models (LLMs). This approach aims to enhance the performance of LLMs by combining outputs from multiple models dynamically during inference, optimizing for accuracy and efficiency in various applications.