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
Artificial Intelligence and the Spatial Documentation of Languages
Hakam Ghanim
Advancing AI with Integrity: Ethical Challenges and Solutions in Neural Machine Translation
Richard Kimera, Yun-Seon Kim, Heeyoul Choi
AIGCOIQA2024: Perceptual Quality Assessment of AI Generated Omnidirectional Images
Liu Yang, Huiyu Duan, Long Teng, Yucheng Zhu, Xiaohong Liu, Menghan Hu, Xiongkuo Min, Guangtao Zhai, Patrick Le Callet
LLM-RadJudge: Achieving Radiologist-Level Evaluation for X-Ray Report Generation
Zilong Wang, Xufang Luo, Xinyang Jiang, Dongsheng Li, Lili Qiu
Rapid Mobile App Development for Generative AI Agents on MIT App Inventor
Jaida Gao, Calab Su, Etai Miller, Kevin Lu, Yu Meng
Generative AI Adoption in Classroom in Context of Technology Acceptance Model (TAM) and the Innovation Diffusion Theory (IDT)
Aashish Ghimire, John Edwards
Distributed agency in second language learning and teaching through generative AI
Robert Godwin-Jones
Implications of the AI Act for Non-Discrimination Law and Algorithmic Fairness
Luca Deck, Jan-Laurin Müller, Conradin Braun, Domenique Zipperling, Niklas Kühl
A comparison of Human, GPT-3.5, and GPT-4 Performance in a University-Level Coding Course
Will Yeadon, Alex Peach, Craig P. Testrow
"It is there, and you need it, so why do you not use it?" Achieving better adoption of AI systems by domain experts, in the case study of natural science research
Auste Simkute, Ewa Luger, Michael Evans, Rhianne Jones
Navigating the EU AI Act: A Methodological Approach to Compliance for Safety-critical Products
J. Kelly, S. Zafar, L. Heidemann, J. Zacchi, D. Espinoza, N. Mata
DeepGleason: a System for Automated Gleason Grading of Prostate Cancer using Deep Neural Networks
Dominik Müller, Philip Meyer, Lukas Rentschler, Robin Manz, Jonas Bäcker, Samantha Cramer, Christoph Wengenmayr, Bruno Märkl, Ralf Huss, Iñaki Soto-Rey, Johannes Raffler
Prompting the E-Brushes: Users as Authors in Generative AI
Yiyang Mei