Error Mitigation

Error mitigation research focuses on reducing inaccuracies in various computational systems, from large language models and quantum computers to image recognition and localization systems. Current efforts utilize diverse approaches, including reinforcement learning for adaptive mitigation, neural networks for noise reduction and error correction, and techniques like data augmentation and prompt engineering to improve model robustness and accuracy. These advancements are crucial for enhancing the reliability and performance of numerous technologies, impacting fields ranging from software development and medical imaging to high-performance computing and communication systems.