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
A Retrospective of the Tutorial on Opportunities and Challenges of Online Deep Learning
Cedric Kulbach, Lucas Cazzonelli, Hoang-Anh Ngo, Minh-Huong Le-Nguyen, Albert Bifet
From Obstacle to Opportunity: Enhancing Semi-supervised Learning with Synthetic Data
Zerun Wang, Jiafeng Mao, Liuyu Xiang, Toshihiko Yamasaki
Risks and Opportunities of Open-Source Generative AI
Francisco Eiras, Aleksandar Petrov, Bertie Vidgen, Christian Schroeder, Fabio Pizzati, Katherine Elkins, Supratik Mukhopadhyay, Adel Bibi, Aaron Purewal, Csaba Botos, Fabro Steibel, Fazel Keshtkar, Fazl Barez, Genevieve Smith, Gianluca Guadagni, Jon Chun, Jordi Cabot, Joseph Imperial, Juan Arturo Nolazco, Lori Landay, Matthew Jackson, Phillip H. S. Torr, Trevor Darrell, Yong Lee, Jakob Foerster
Challenges and Opportunities in Text Generation Explainability
Kenza Amara, Rita Sevastjanova, Mennatallah El-Assady
Open Challenges and Opportunities in Federated Foundation Models Towards Biomedical Healthcare
Xingyu Li, Lu Peng, Yuping Wang, Weihua Zhang
Opportunities for Persian Digital Humanities Research with Artificial Intelligence Language Models; Case Study: Forough Farrokhzad
Arash Rasti Meymandi, Zahra Hosseini, Sina Davari, Abolfazl Moshiri, Shabnam Rahimi-Golkhandan, Khashayar Namdar, Nikta Feizi, Mohamad Tavakoli-Targhi, Farzad Khalvati
ChatGPTest: opportunities and cautionary tales of utilizing AI for questionnaire pretesting
Francisco Olivos, Minhui Liu