Design Principle
Design principles in artificial intelligence and related fields focus on establishing guidelines for creating effective and efficient systems. Current research emphasizes improving model architectures and algorithms through techniques like incorporating design rationales into prompts (for program repair), transferring design principles via large language models (for neural architecture search), and optimizing resource allocation (e.g., cache mechanisms for graph neural network training). These advancements aim to enhance performance, reduce computational costs, and improve the interpretability and robustness of AI systems, impacting diverse applications from software engineering to medical imaging and robotics.
Papers
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