Technical Challenge
Research into technical challenges across diverse AI applications reveals a common thread: improving model robustness, fairness, and explainability while addressing limitations in data availability and computational efficiency. Current efforts focus on developing and adapting model architectures (e.g., LLMs, YOLO variants, diffusion models) for specific tasks, refining evaluation metrics, and designing robust training and deployment strategies (e.g., federated learning). These advancements are crucial for ensuring the responsible and effective deployment of AI in various sectors, from healthcare and finance to manufacturing and environmental monitoring.
Papers
A Perspective for Adapting Generalist AI to Specialized Medical AI Applications and Their Challenges
Zifeng Wang, Hanyin Wang, Benjamin Danek, Ying Li, Christina Mack, Hoifung Poon, Yajuan Wang, Pranav Rajpurkar, Jimeng Sun
A Systematic Review of Machine Learning in Sports Betting: Techniques, Challenges, and Future Directions
René Manassé Galekwa, Jean Marie Tshimula, Etienne Gael Tajeuna, Kyamakya Kyandoghere
Document Parsing Unveiled: Techniques, Challenges, and Prospects for Structured Information Extraction
Qintong Zhang, Victor Shea-Jay Huang, Bin Wang, Junyuan Zhang, Zhengren Wang, Hao Liang, Shawn Wang, Matthieu Lin, Wentao Zhang, Conghui He
AI-Driven Human-Autonomy Teaming in Tactical Operations: Proposed Framework, Challenges, and Future Directions
Desta Haileselassie Hagos, Hassan El Alami, Danda B. Rawat
From Cool Demos to Production-Ready FMware: Core Challenges and a Technology Roadmap
Gopi Krishnan Rajbahadur, Gustavo A. Oliva, Dayi Lin, Ahmed E. Hassan
OReole-FM: successes and challenges toward billion-parameter foundation models for high-resolution satellite imagery
Philipe Dias, Aristeidis Tsaris, Jordan Bowman, Abhishek Potnis, Jacob Arndt, H. Lexie Yang, Dalton Lunga
Natural Language Processing for the Legal Domain: A Survey of Tasks, Datasets, Models, and Challenges
Farid Ariai, Gianluca Demartini
Watermarking Large Language Models and the Generated Content: Opportunities and Challenges
Ruisi Zhang, Farinaz Koushanfar
Adapting MLOps for Diverse In-Network Intelligence in 6G Era: Challenges and Solutions
Peizheng Li, Ioannis Mavromatis, Tim Farnham, Adnan Aijaz, Aftab Khan
Beyond Multiple-Choice Accuracy: Real-World Challenges of Implementing Large Language Models in Healthcare
Yifan Yang, Qiao Jin, Qingqing Zhu, Zhizheng Wang, Francisco Erramuspe Álvarez, Nicholas Wan, Benjamin Hou, Zhiyong Lu
Position: Challenges and Opportunities for Differential Privacy in the U.S. Federal Government
Amol Khanna, Adam McCormick, Andre Nguyen, Chris Aguirre, Edward Raff
Limpeh ga li gong: Challenges in Singlish Annotations
Luo Qi Chan, Lynnette Hui Xian Ng
On-Device LLMs for SMEs: Challenges and Opportunities
Jeremy Stephen Gabriel Yee Zhi Wen, Pai Chet Ng, Zhengkui Wang, Ian McLoughlin, Aik Beng Ng, Simon See
Opportunities and Challenges of Generative-AI in Finance
Akshar Prabhu Desai, Ganesh Satish Mallya, Mohammad Luqman, Tejasvi Ravi, Nithya Kota, Pranjul Yadav
Which LLMs are Difficult to Detect? A Detailed Analysis of Potential Factors Contributing to Difficulties in LLM Text Detection
Shantanu Thorat, Tianbao Yang
Measuring Diversity: Axioms and Challenges
Mikhail Mironov, Liudmila Prokhorenkova
Critical Questions Generation: Motivation and Challenges
Blanca Calvo Figueras, Rodrigo Agerri