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
Embodied Exploration of Latent Spaces and Explainable AI
Elizabeth Wilson, Mika Satomi, Alex McLean, Deva Schubert, Juan Felipe Amaya Gonzalez
AI on My Shoulder: Supporting Emotional Labor in Front-Office Roles with an LLM-based Empathetic Coworker
Vedant Das Swain, Qiuyue "Joy" Zhong, Jash Rajesh Parekh, Yechan Jeon, Roy Zimmerman, Mary Czerwinski, Jina Suh, Varun Mishra, Koustuv Saha, Javier Hernandez
Human-Centric eXplainable AI in Education
Subhankar Maity, Aniket Deroy
Generative AI, Pragmatics, and Authenticity in Second Language Learning
Robert Godwin-Jones`
Assistive AI for Augmenting Human Decision-making
Natabara Máté Gyöngyössy, Bernát Török, Csilla Farkas, Laura Lucaj, Attila Menyhárd, Krisztina Menyhárd-Balázs, András Simonyi, Patrick van der Smagt, Zsolt Ződi, András Lőrincz
LLM Agent Honeypot: Monitoring AI Hacking Agents in the Wild
Reworr, Dmitrii Volkov
Automating IETF Insights generation with AI
Jaime Jiménez
Perceptions of Discriminatory Decisions of Artificial Intelligence: Unpacking the Role of Individual Characteristics
Soojong Kim
From chalkboards to chatbots: SELAR assists teachers in embracing AI in the curriculum
Hani Alers, Aleksandra Malinowska, Mathis Mourey, Jasper Waaijer
Adversarial Neural Networks in Medical Imaging Advancements and Challenges in Semantic Segmentation
Houze Liu, Bo Zhang, Yanlin Xiang, Yuxiang Hu, Aoran Shen, Yang Lin
To Err is AI : A Case Study Informing LLM Flaw Reporting Practices
Sean McGregor, Allyson Ettinger, Nick Judd, Paul Albee, Liwei Jiang, Kavel Rao, Will Smith, Shayne Longpre, Avijit Ghosh, Christopher Fiorelli, Michelle Hoang, Sven Cattell, Nouha Dziri
Integrating Artificial Intelligence Models and Synthetic Image Data for Enhanced Asset Inspection and Defect Identification
Reddy Mandati, Vladyslav Anderson, Po-chen Chen, Ankush Agarwal, Tatjana Dokic, David Barnard, Michael Finn, Jesse Cromer, Andrew Mccauley, Clay Tutaj, Neha Dave, Bobby Besharati, Jamie Barnett, Timothy Krall
Evidence of Cognitive Deficits andDevelopmental Advances in Generative AI: A Clock Drawing Test Analysis
Isaac R. Galatzer-Levy, Jed McGiffin, David Munday, Xin Liu, Danny Karmon, Ilia Labzovsky, Rivka Moroshko, Amir Zait, Daniel McDuff
Advancements in Visual Language Models for Remote Sensing: Datasets, Capabilities, and Enhancement Techniques
Lijie Tao, Haokui Zhang, Haizhao Jing, Yu Liu, Kelu Yao, Chao Li, Xizhe Xue
Towards a Healthy AI Tradition: Lessons from Biology and Biomedical Science
Simon Kasif
Machine Learning via rough mereology
Lech T. Polkowski