User Attention

User attention research investigates how individuals focus on information, particularly within complex interfaces and during interactions with AI systems. Current studies explore how attention is influenced by factors like cognitive load and visual cues, employing techniques such as eye-tracking and analyzing attention mechanisms within large language models (LLMs) and other AI architectures like contextual bandits. This research is crucial for improving user experience design in various applications, from e-commerce platforms to code generation tools, by optimizing information presentation and predicting user behavior. Understanding and modeling user attention is key to building more efficient and effective AI systems and user interfaces.