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 Language Models in Modern Healthcare: A Comprehensive Review
Amna Khalid, Ayma Khalid, Umar Khalid
On the role of Artificial Intelligence methods in modern force-controlled manufacturing robotic tasks
Vincenzo Petrone, Enrico Ferrentino, Pasquale Chiacchio
RoleBreak: Character Hallucination as a Jailbreak Attack in Role-Playing Systems
Yihong Tang, Bo Wang, Xu Wang, Dongming Zhao, Jing Liu, Jijun Zhang, Ruifang He, Yuexian Hou
The Role of Deep Learning Regularizations on Actors in Offline RL
Denis Tarasov, Anja Surina, Caglar Gulcehre
The Role of Explainable AI in Revolutionizing Human Health Monitoring
Abdullah Alharthi, Ahmed Alqurashi, Turki Alharbi, Mohammed Alammar, Nasser Aldosari, Houssem Bouchekara, Yusuf Shaaban, Mohammad Shoaib Shahriar, Abdulrahman Al Ayidh
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