Frontend Component Code
Frontend component code research focuses on improving the efficiency and effectiveness of creating and managing user interface elements. Current efforts concentrate on automating code generation using machine learning models, particularly transformer-based architectures, often leveraging techniques like reinforcement learning and program decomposition to enhance accuracy and reduce development time. This research is significant because it promises to streamline web application development, potentially improving software quality and reducing development costs across various applications.
Papers
ReACT: Reinforcement Learning for Controller Parametrization using B-Spline Geometries
Thomas Rudolf, Daniel Flögel, Tobias Schürmann, Simon Süß, Stefan Schwab, Sören Hohmann
REACT 2024: the Second Multiple Appropriate Facial Reaction Generation Challenge
Siyang Song, Micol Spitale, Cheng Luo, Cristina Palmero, German Barquero, Hengde Zhu, Sergio Escalera, Michel Valstar, Tobias Baur, Fabien Ringeval, Elisabeth Andre, Hatice Gunes