Emerging Opportunity
Emerging research highlights the transformative potential of artificial intelligence across diverse fields, focusing on optimizing AI model fairness, leveraging AI for resource management and efficiency gains (e.g., congestion pricing), and developing AI-powered tools for various applications including healthcare, education, and scientific discovery. Current research emphasizes improving model interpretability, robustness, and addressing ethical concerns related to bias and transparency, often utilizing large language models (LLMs) and deep learning architectures. This work holds significant implications for advancing scientific understanding, improving decision-making processes, and creating more efficient and equitable systems across numerous sectors.
Papers
Artificial Intelligence in Bone Metastasis Analysis: Current Advancements, Opportunities and Challenges
Marwa Afnouch, Fares Bougourzi, Olfa Gaddour, Fadi Dornaika, Abdelmalik Taleb-Ahmed
A critical appraisal of water table depth estimation: Challenges and opportunities within machine learning
Joseph Janssen, Ardalan Tootchi, Ali A. Ameli
Near to Mid-term Risks and Opportunities of Open-Source Generative AI
Francisco Eiras, Aleksandar Petrov, Bertie Vidgen, Christian Schroeder de Witt, Fabio Pizzati, Katherine Elkins, Supratik Mukhopadhyay, Adel Bibi, Botos Csaba, Fabro Steibel, Fazl Barez, Genevieve Smith, Gianluca Guadagni, Jon Chun, Jordi Cabot, Joseph Marvin Imperial, Juan A. Nolazco-Flores, Lori Landay, Matthew Jackson, Paul Röttger, Philip H. S. Torr, Trevor Darrell, Yong Suk Lee, Jakob Foerster
Fake Artificial Intelligence Generated Contents (FAIGC): A Survey of Theories, Detection Methods, and Opportunities
Xiaomin Yu, Yezhaohui Wang, Yanfang Chen, Zhen Tao, Dinghao Xi, Shichao Song, Simin Niu, Zhiyu Li
When Fuzzing Meets LLMs: Challenges and Opportunities
Yu Jiang, Jie Liang, Fuchen Ma, Yuanliang Chen, Chijin Zhou, Yuheng Shen, Zhiyong Wu, Jingzhou Fu, Mingzhe Wang, ShanShan Li, Quan Zhang