Artificial Intelligence Model
Artificial intelligence (AI) models are rapidly evolving, with current research focusing on improving their reliability, security, and fairness. Key areas of investigation include mitigating model errors (including adversarial attacks), ensuring robustness across diverse datasets and contexts, and addressing biases that may lead to unfair or culturally insensitive outputs. These advancements are crucial for building trust in AI systems and enabling their safe and effective deployment across various sectors, from healthcare and finance to manufacturing and autonomous systems.
Papers
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September 9, 2023
Towards LLM-based Autograding for Short Textual Answers
Johannes Schneider, Bernd Schenk, Christina Niklaus, Michaelis Vlachos
Beyond Traditional Teaching: The Potential of Large Language Models and Chatbots in Graduate Engineering Education
Mahyar Abedi, Ibrahem Alshybani, Muhammad Rubayat Bin Shahadat, Michael S. Murillo
September 4, 2023
August 31, 2023