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
Decentralized Multi-Party Multi-Network AI for Global Deployment of 6G Wireless Systems
Merim Dzaferagic, Marco Ruffini, Nina Slamnik-Krijestorac, Joao F. Santos, Johann Marquez-Barja, Christos Tranoris, Spyros Denazis, Thomas Kyriakakis, Panagiotis Karafotis, Luiz DaSilva, Shashi Raj Pandey, Junya Shiraishi, Petar Popovski, Soren Kejser Jensen, Christian Thomsen, Torben Bach Pedersen, Holger Claussen, Jinfeng Du, Gil Zussman, Tingjun Chen, Yiran Chen, Seshu Tirupathi, Ivan Seskar, Daniel Kilper
Hybrid Intelligence for Digital Humanities
Victor de Boer, Lise Stork
AI Competitions and Benchmarks: Dataset Development
Romain Egele, Julio C. S. Jacques Junior, Jan N. van Rijn, Isabelle Guyon, Xavier Baró, Albert Clapés, Prasanna Balaprakash, Sergio Escalera, Thomas Moeslund, Jun Wan
Listen to the Waves: Using a Neuronal Model of the Human Auditory System to Predict Ocean Waves
Artur Matysiak, Volker Roeber, Henrik Kalisch, Reinhard König, Patrick J. C. May
Can AI Understand Our Universe? Test of Fine-Tuning GPT by Astrophysical Data
Yu Wang, Shu-Rui Zhang, Aidin Momtaz, Rahim Moradi, Fatemeh Rastegarnia, Narek Sahakyan, Soroush Shakeri, Liang Li
Affirmative safety: An approach to risk management for high-risk AI
Akash R. Wasil, Joshua Clymer, David Krueger, Emily Dardaman, Simeon Campos, Evan R. Murphy
Artificial Intelligence enhanced Security Problems in Real-Time Scenario using Blowfish Algorithm
Yuvaraju Chinnam, Bosubabu Sambana
Uncertainty Quantification in Detecting Choroidal Metastases on MRI via Evolutionary Strategies
Bala McRae-Posani, Andrei Holodny, Hrithwik Shalu, Joseph N Stember
The Path To Autonomous Cyber Defense
Sean Oesch, Phillipe Austria, Amul Chaulagain, Brian Weber, Cory Watson, Matthew Dixson, Amir Sadovnik
Mitigating Challenges of the Space Environment for Onboard Artificial Intelligence: Design Overview of the Imaging Payload on SpIRIT
Miguel Ortiz del Castillo, Jonathan Morgan, Jack McRobbie, Clint Therakam, Zaher Joukhadar, Robert Mearns, Simon Barraclough, Richard Sinnott, Andrew Woods, Chris Bayliss, Kris Ehinger, Ben Rubinstein, James Bailey, Airlie Chapman, Michele Trenti
Artificial Intelligence in Everyday Life 2.0: Educating University Students from Different Majors
Maria Kasinidou, Styliani Kleanthous, Matteo Busso, Marcelo Rodas, Jahna Otterbacher, Fausto Giunchiglia
The Transformation Risk-Benefit Model of Artificial Intelligence: Balancing Risks and Benefits Through Practical Solutions and Use Cases
Richard Fulton, Diane Fulton, Nate Hayes, Susan Kaplan
The Necessity of AI Audit Standards Boards
David Manheim, Sammy Martin, Mark Bailey, Mikhail Samin, Ross Greutzmacher
Unraveling the Dilemma of AI Errors: Exploring the Effectiveness of Human and Machine Explanations for Large Language Models
Marvin Pafla, Kate Larson, Mark Hancock
Untangling Critical Interaction with AI in Students Written Assessment
Antonette Shibani, Simon Knight, Kirsty Kitto, Ajanie Karunanayake, Simon Buckingham Shum
A Survey on the Integration of Generative AI for Critical Thinking in Mobile Networks
Athanasios Karapantelakis, Alexandros Nikou, Ajay Kattepur, Jean Martins, Leonid Mokrushin, Swarup Kumar Mohalik, Marin Orlic, Aneta Vulgarakis Feljan
Incremental XAI: Memorable Understanding of AI with Incremental Explanations
Jessica Y. Bo, Pan Hao, Brian Y. Lim
Racial/Ethnic Categories in AI and Algorithmic Fairness: Why They Matter and What They Represent
Jennifer Mickel
From Protoscience to Epistemic Monoculture: How Benchmarking Set the Stage for the Deep Learning Revolution
Bernard J. Koch, David Peterson
Advancements in Radiomics and Artificial Intelligence for Thyroid Cancer Diagnosis
Milad Yousefi, Shadi Farabi Maleki, Ali Jafarizadeh, Mahya Ahmadpour Youshanlui, Aida Jafari, Siamak Pedrammehr, Roohallah Alizadehsani, Ryszard Tadeusiewicz, Pawel Plawiak