Human Rating

Human rating, the process of assigning numerical or categorical scores to data, is crucial for evaluating and improving various AI systems, particularly large language models and recommender systems. Current research focuses on developing robust and efficient rating methods, including those leveraging graph neural networks, probabilistic matrix factorization, and novel approaches like Best-Worst Scaling, to address challenges such as data sparsity, bias, and the need for scalable evaluation. These advancements aim to enhance the accuracy and reliability of AI-generated content and recommendations, ultimately improving the user experience and facilitating more informed decision-making across diverse applications.