Research on the Innovative Framework and Application of Large Language Models in Cross Modal Tasks
Y.T. Ji, Guohua Zhu, Yifan Wang, Zhen Tian, Yaoxuan Liang · 2025
As a focus in the field of artificial intelligence in recent years, Large Language Models (LLMs) have the ability to generate human readable natural language by learning massive amounts of text data, and have achieved remarkable results in natural language processing tasks such as machine translation, dialogue generation, and question answering systems. However, its development has not been smooth sailing, facing many challenges such as lack of reasoning ability, bias and bias, and weak model interpretability. Finally, looking forward to the future development trends of big language models, including improving generalization ability, enhancing interpretability, and innovative ideas in privacy protection, ethical security, and other aspects. Intended to provide comprehensive and in-depth analysis and recommendations for the research and application of large language models, helping to promote the continuous progress of natural language processing technology.