Integral Role
Research on the "role" of various components in complex systems focuses on understanding their contributions to overall system performance and behavior. Current investigations span diverse fields, examining the impact of factors like data embedding strategies in quantum computing, prompt engineering in large language models, and architectural choices in deep learning for improved generalization and efficiency. These studies are crucial for optimizing existing systems and developing new ones, with implications ranging from enhancing AI safety and healthcare applications to improving manufacturing processes and scientific discovery.
Papers
The role of data embedding in quantum autoencoders for improved anomaly detection
Jack Y. Araz, Michael Spannowsky
The Role of Graph Topology in the Performance of Biomedical Knowledge Graph Completion Models
Alberto Cattaneo, Stephen Bonner, Thomas Martynec, Carlo Luschi, Ian P Barrett, Daniel Justus
On The Role of Prompt Construction In Enhancing Efficacy and Efficiency of LLM-Based Tabular Data Generation
Banooqa Banday, Kowshik Thopalli, Tanzima Z. Islam, Jayaraman J. Thiagarajan