The SCE (Scalable Consistency Ensemble) framework enables efficient combination of multiple LLMs to generate more reliable responses without the typical computational overhead.

• Leverages the diverse strengths of different language models while minimizing their individual weaknesses
• Implements a systematic approach to prompt consistency across multiple models
• Achieves improved reliability while maintaining computational efficiency
• Addresses critical security concerns by enhancing trustworthiness in AI outputs

This research is particularly valuable for security applications where inconsistent or unreliable AI responses could lead to vulnerabilities or misinformation, providing a practical engineering solution for more dependable AI systems.

SCE: Scalable Consistency Ensembles Make Blackbox Large Language Model Generation More Reliable