Forgotten ReaLM
Research into "Realms" focuses on integrating diverse data modalities and leveraging advanced algorithms to improve model performance and understanding in various domains. Current efforts concentrate on enhancing sample efficiency in reinforcement learning through human-in-the-loop approaches and developing robust models for processing multimodal data like electronic health records and speech signals, often employing large language models and neural networks. This work is significant for advancing AI capabilities in robotics, healthcare, and other fields by improving the accuracy, efficiency, and explainability of complex systems.
Papers
September 23, 2024
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November 10, 2022