By TheStaff 
Large Language Models (LLMs) such as GPT, Gemini, and Claude utilize vast training datasets and complex architectures to generate high-quality responses. However, optimizing their inference-time computation remains challenging, as increasing model size leads to higher computational costs. Researchers continue to explore strategies that maximize efficiency while maintaining or improving model performance. One widely adopted approach […]
The post Princeton University Researchers Introduce Self-MoA and Self-MoA-Seq: Optimizing LLM Performance with Single-Model Ensembles appeared first on MarkTechPost.