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
When Are Combinations of Humans and AI Useful?
Michelle Vaccaro, Abdullah Almaatouq, Thomas Malone
Artificial Intelligence as the New Hacker: Developing Agents for Offensive Security
Leroy Jacob Valencia
Artificial intelligence for abnormality detection in high volume neuroimaging: a systematic review and meta-analysis
Siddharth Agarwal, David A. Wood, Mariusz Grzeda, Chandhini Suresh, Munaib Din, James Cole, Marc Modat, Thomas C Booth
People cannot distinguish GPT-4 from a human in a Turing test
Cameron R. Jones, Benjamin K. Bergen
Synthetic Data in Radiological Imaging: Current State and Future Outlook
Elena Sizikova, Andreu Badal, Jana G. Delfino, Miguel Lago, Brandon Nelson, Niloufar Saharkhiz, Berkman Sahiner, Ghada Zamzmi, Aldo Badano
The Potential and Implications of Generative AI on HCI Education
Ahmed Kharrufa, Ian G Johnson
Overcoming Anchoring Bias: The Potential of AI and XAI-based Decision Support
Felix Haag, Carlo Stingl, Katrin Zerfass, Konstantin Hopf, Thorsten Staake
Developing trustworthy AI applications with foundation models
Michael Mock, Sebastian Schmidt, Felix Müller, Rebekka Görge, Anna Schmitz, Elena Haedecke, Angelika Voss, Dirk Hecker, Maximillian Poretschkin
AI in Lung Health: Benchmarking Detection and Diagnostic Models Across Multiple CT Scan Datasets
Fakrul Islam Tushar, Avivah Wang, Lavsen Dahal, Michael R. Harowicz, Kyle J. Lafata, Tina D. Tailor, Joseph Y. Lo
Enhancing the Efficiency and Accuracy of Underlying Asset Reviews in Structured Finance: The Application of Multi-agent Framework
Xiangpeng Wan, Haicheng Deng, Kai Zou, Shiqi Xu
Lumbar Spine Tumor Segmentation and Localization in T2 MRI Images Using AI
Rikathi Pal, Sudeshna Mondal, Aditi Gupta, Priya Saha, Somoballi Ghoshal, Amlan Chakrabarti, Susmita Sur-Kolay
The Elephant in the Room -- Why AI Safety Demands Diverse Teams
David Rostcheck, Lara Scheibling
NeurDB: An AI-powered Autonomous Data System
Beng Chin Ooi, Shaofeng Cai, Gang Chen, Yanyan Shen, Kian-Lee Tan, Yuncheng Wu, Xiaokui Xiao, Naili Xing, Cong Yue, Lingze Zeng, Meihui Zhang, Zhanhao Zhao
Interpretable Data Fusion for Distributed Learning: A Representative Approach via Gradient Matching
Mengchen Fan, Baocheng Geng, Keren Li, Xueqian Wang, Pramod K. Varshney
Sora and V-JEPA Have Not Learned The Complete Real World Model -- A Philosophical Analysis of Video AIs Through the Theory of Productive Imagination
Jianqiu Zhang
Research information in the light of artificial intelligence: quality and data ecologies
Otmane Azeroual, Tibor Koltay
Artificial Intelligence in the Autonomous Navigation of Endovascular Interventions: A Systematic Review
Harry Robertshaw, Lennart Karstensen, Benjamin Jackson, Hadi Sadati, Kawal Rhode, Sebastien Ourselin, Alejandro Granados, Thomas C Booth
Vietnamese AI Generated Text Detection
Quang-Dan Tran, Van-Quan Nguyen, Quang-Huy Pham, K. B. Thang Nguyen, Trong-Hop Do