Strong Model

"Strong model" research focuses on understanding and leveraging the capabilities of highly performant machine learning models, particularly large language models, while addressing challenges related to their explainability, alignment with human values, and training efficiency. Current research emphasizes techniques like weak-to-strong learning, where less capable models guide the training of stronger ones, and explores methods to mitigate issues such as bias amplification and model deception. These advancements are crucial for building reliable and trustworthy AI systems, improving their interpretability, and enabling their safe and effective deployment in various applications.