Artificial Intelligence
Artificial intelligence (AI) research focuses on creating systems capable of performing tasks that typically require human intelligence, with current efforts concentrating on improving model alignment with human values, enhancing transparency and accountability in AI systems, and mitigating risks associated with bias and malicious use. Prominent approaches involve large language models (LLMs), deep learning architectures like nnU-Net, and reinforcement learning techniques, often applied within specific domains such as healthcare, cybersecurity, and scientific research. The widespread adoption of AI across diverse fields necessitates rigorous investigation into its ethical implications, safety, and societal impact, driving ongoing research to develop more robust, reliable, and responsible AI systems.
Papers
Advanced AI Framework for Enhanced Detection and Assessment of Abdominal Trauma: Integrating 3D Segmentation with 2D CNN and RNN Models
Liheng Jiang, Xuechun yang, Chang Yu, Zhizhong Wu, Yuting Wang
Artificial Intelligence in Extracting Diagnostic Data from Dental Records
Yao-Shun Chuang, Chun-Teh Lee, Oluwabunmi Tokede, Guo-Hao Lin, Ryan Brandon, Trung Duong Tran, Xiaoqian Jiang, Muhammad F. Walji
AI for Handball: predicting and explaining the 2024 Olympic Games tournament with Deep Learning and Large Language Models
Florian Felice
The Contribution of XAI for the Safe Development and Certification of AI: An Expert-Based Analysis
Benjamin Fresz, Vincent Philipp Göbels, Safa Omri, Danilo Brajovic, Andreas Aichele, Janika Kutz, Jens Neuhüttler, Marco F. Huber
Problems in AI, their roots in philosophy, and implications for science and society
Max Velthoven, Eric Marcus
A Survey of AI Reliance
Sven Eckhardt, Niklas Kühl, Mateusz Dolata, Gerhard Schwabe
Automated Road Safety: Enhancing Sign and Surface Damage Detection with AI
Davide Merolla, Vittorio Latorre, Antonio Salis, Gianluca Boanelli
Imposter.AI: Adversarial Attacks with Hidden Intentions towards Aligned Large Language Models
Xiao Liu, Liangzhi Li, Tong Xiang, Fuying Ye, Lu Wei, Wangyue Li, Noa Garcia
Building Machines that Learn and Think with People
Katherine M. Collins, Ilia Sucholutsky, Umang Bhatt, Kartik Chandra, Lionel Wong, Mina Lee, Cedegao E. Zhang, Tan Zhi-Xuan, Mark Ho, Vikash Mansinghka, Adrian Weller, Joshua B. Tenenbaum, Thomas L. Griffiths
Nonlinear Schr\"odinger Network
Yiming Zhou, Callen MacPhee, Tingyi Zhou, Bahram Jalali
AI for All: Identifying AI incidents Related to Diversity and Inclusion
Rifat Ara Shams, Didar Zowghi, Muneera Bano
Integrating Artificial Intelligence into Operating Systems: A Comprehensive Survey on Techniques, Applications, and Future Directions
Yifan Zhang, Xinkui Zhao, Ziying Li, Jianwei Yin, Lufei Zhang, Zuoning Chen
Assurance of AI Systems From a Dependability Perspective
Robin Bloomfield, John Rushby
APS-USCT: Ultrasound Computed Tomography on Sparse Data via AI-Physic Synergy
Yi Sheng, Hanchen Wang, Yipei Liu, Junhuan Yang, Weiwen Jiang, Youzuo Lin, Lei Yang
Baba Is AI: Break the Rules to Beat the Benchmark
Nathan Cloos, Meagan Jens, Michelangelo Naim, Yen-Ling Kuo, Ignacio Cases, Andrei Barbu, Christopher J. Cueva
Predicting Star Scientists in the Field of Artificial Intelligence: A Machine Learning Approach
Koosha Shirouyeh, Andrea Schiffauerova, Ashkan Ebadi