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EyeFormer - Predicting Personalized Scanpaths with Transformer-Guided Reinforcement Learning

Association for Computing Machinery (ACM) via YouTube

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Watch a 16-minute conference talk from the 37th Annual ACM Symposium on User Interface Software and Technology (UIST 2024) exploring an innovative approach to predicting personalized eye movement patterns using a combination of transformer architecture and reinforcement learning techniques. Learn about cutting-edge research in user interface technology that focuses on understanding and anticipating individual user gaze behavior, presented at this prestigious ACM conference in Pittsburgh, PA.

Syllabus

EyeFormer: Predicting Personalized Scanpaths with Transformer-Guided Reinforcement Learning

Taught by

ACM SIGCHI

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