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
KAN 2.0: Kolmogorov-Arnold Networks Meet Science
Ziming Liu, Pingchuan Ma, Yixuan Wang, Wojciech Matusik, Max Tegmark
Envisioning Possibilities and Challenges of AI for Personalized Cancer Care
Elaine Kong, Kuo-Ting, Huang, Aakash Gautam
Towards Few-Shot Learning in the Open World: A Review and Beyond
Hui Xue, Yuexuan An, Yongchun Qin, Wenqian Li, Yixin Wu, Yongjuan Che, Pengfei Fang, Minling Zhang
Speaking the Same Language: Leveraging LLMs in Standardizing Clinical Data for AI
Arindam Sett, Somaye Hashemifar, Mrunal Yadav, Yogesh Pandit, Mohsen Hejrati
On the Undecidability of Artificial Intelligence Alignment: Machines that Halt
Gabriel Adriano de Melo, Marcos Ricardo Omena De Albuquerque Maximo, Nei Yoshihiro Soma, Paulo Andre Lima de Castro
Beyond the Hype: A dispassionate look at vision-language models in medical scenario
Yang Nan, Huichi Zhou, Xiaodan Xing, Guang Yang
Navigating the sociotechnical labyrinth: Dynamic certification for responsible embodied AI
Georgios Bakirtzis, Andrea Aler Tubella, Andreas Theodorou, David Danks, Ufuk Topcu
A theory of understanding for artificial intelligence: composability, catalysts, and learning
Zijian Zhang, Sara Aronowitz, Alán Aspuru-Guzik
Enhancing Equitable Access to AI in Housing and Homelessness System of Care through Federated Learning
Musa Taib, Jiajun Wu, Steve Drew, Geoffrey G. Messier
The AI Risk Repository: A Comprehensive Meta-Review, Database, and Taxonomy of Risks From Artificial Intelligence
Peter Slattery, Alexander K. Saeri, Emily A. C. Grundy, Jess Graham, Michael Noetel, Risto Uuk, James Dao, Soroush Pour, Stephen Casper, Neil Thompson
An Introduction to Reinforcement Learning: Fundamental Concepts and Practical Applications
Majid Ghasemi, Amir Hossein Moosavi, Ibrahim Sorkhoh, Anjali Agrawal, Fadi Alzhouri, Dariush Ebrahimi
HADRON: Human-friendly Control and Artificial Intelligence for Military Drone Operations
Ana M. Casado Faulí, Mario Malizia, Ken Hasselmann, Emile Le Flécher, Geert De Cubber, Ben Lauwens
PathInsight: Instruction Tuning of Multimodal Datasets and Models for Intelligence Assisted Diagnosis in Histopathology
Xiaomin Wu, Rui Xu, Pengchen Wei, Wenkang Qin, Peixiang Huang, Ziheng Li, Lin Luo
Generative AI Tools in Academic Research: Applications and Implications for Qualitative and Quantitative Research Methodologies
Mike Perkins, Jasper Roe
AI Research is not Magic, it has to be Reproducible and Responsible: Challenges in the AI field from the Perspective of its PhD Students
Andrea Hrckova, Jennifer Renoux, Rafael Tolosana Calasanz, Daniela Chuda, Martin Tamajka, Jakub Simko
The AI Scientist: Towards Fully Automated Open-Ended Scientific Discovery
Chris Lu, Cong Lu, Robert Tjarko Lange, Jakob Foerster, Jeff Clune, David Ha
How ChatGPT Changed the Media's Narratives on AI: A Semi-Automated Narrative Analysis Through Frame Semantics
Igor Ryazanov, Carl Öhman, Johanna Björklund
Synthetic Photography Detection: A Visual Guidance for Identifying Synthetic Images Created by AI
Melanie Mathys, Marco Willi, Raphael Meier