Helpfulness Score

Helpfulness scores assess the utility and value of responses generated by large language models (LLMs) and other systems, aiming to optimize for both user satisfaction and safety. Current research focuses on improving these scores through techniques like reinforcement learning from AI and human feedback, refined attention mechanisms in multimodal models, and incorporating factors such as reviewer expertise and cultural context. This research is crucial for enhancing the reliability and trustworthiness of LLMs, impacting areas such as e-commerce, open-source software development, and the broader field of human-computer interaction.