Prompt Ensemble

Prompt ensemble techniques aim to improve the performance of large language models (LLMs) and other deep learning models by combining the outputs or inputs from multiple prompts, mitigating individual prompt biases and enhancing overall robustness. Current research focuses on developing efficient methods for selecting, weighting, and combining prompts, including hierarchical prompting for high-resolution image generation and boosted ensemble methods for improved reasoning capabilities. These advancements are significant because they enhance the accuracy and reliability of LLMs across diverse tasks, from image generation and machine translation to query reformulation and zero-shot classification, without requiring extensive retraining.