Tuned Lm

Tuned Large Language Models (LLMs) focus on improving the performance and reliability of pre-trained LLMs for specific tasks or domains. Current research emphasizes efficient tuning methods, such as proxy-tuning and sparse pre-training, to reduce computational costs and address issues like hallucination and knowledge limitations. These advancements are significant because they enable the creation of more accurate, efficient, and trustworthy LLMs for diverse applications, ranging from biomedical research to improved educational tools and more reliable code generation.