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
Culturally-Attuned Moral Machines: Implicit Learning of Human Value Systems by AI through Inverse Reinforcement Learning
Nigini Oliveira, Jasmine Li, Koosha Khalvati, Rodolfo Cortes Barragan, Katharina Reinecke, Andrew N. Meltzoff, Rajesh P. N. Rao
EHR Interaction Between Patients and AI: NoteAid EHR Interaction
Xiaocheng Zhang, Zonghai Yao, Hong Yu
Generating Rhythm Game Music with Jukebox
Nicholas Yan
Measuring Value Alignment
Fazl Barez, Philip Torr
Towards Efficient Generative Large Language Model Serving: A Survey from Algorithms to Systems
Xupeng Miao, Gabriele Oliaro, Zhihao Zhang, Xinhao Cheng, Hongyi Jin, Tianqi Chen, Zhihao Jia
Human-AI Collaboration in Real-World Complex Environment with Reinforcement Learning
Md Saiful Islam, Srijita Das, Sai Krishna Gottipati, William Duguay, Clodéric Mars, Jalal Arabneydi, Antoine Fagette, Matthew Guzdial, Matthew-E-Taylor
Pangu-Agent: A Fine-Tunable Generalist Agent with Structured Reasoning
Filippos Christianos, Georgios Papoudakis, Matthieu Zimmer, Thomas Coste, Zhihao Wu, Jingxuan Chen, Khyati Khandelwal, James Doran, Xidong Feng, Jiacheng Liu, Zheng Xiong, Yicheng Luo, Jianye Hao, Kun Shao, Haitham Bou-Ammar, Jun Wang
Improving Task Instructions for Data Annotators: How Clear Rules and Higher Pay Increase Performance in Data Annotation in the AI Economy
Johann Laux, Fabian Stephany, Alice Liefgreen
The Global Impact of AI-Artificial Intelligence: Recent Advances and Future Directions, A Review
Chandregowda Pachegowda
Online Handbook of Argumentation for AI: Volume 4
Lars Bengel, Lydia Blümel, Elfia Bezou-Vrakatseli, Federico Castagna, Giulia D'Agostino, Isabelle Kuhlmann, Jack Mumford, Daphne Odekerken, Fabrizio Russo, Stefan Sarkadi, Madeleine Waller, Andreas Xydis
The Key Artificial Intelligence Technologies in Early Childhood Education: A Review
Yi Honghu, Liu Ting, Lan Gongjin
Big Tech influence over AI research revisited: memetic analysis of attribution of ideas to affiliation
Stanisław Giziński, Paulina Kaczyńska, Hubert Ruczyński, Emilia Wiśnios, Bartosz Pieliński, Przemysław Biecek, Julian Sienkiewicz
Integration and Performance Analysis of Artificial Intelligence and Computer Vision Based on Deep Learning Algorithms
Bo Liu, Liqiang Yu, Chang Che, Qunwei Lin, Hao Hu, Xinyu Zhao
Human-Centred Learning Analytics and AI in Education: a Systematic Literature Review
Riordan Alfredo, Vanessa Echeverria, Yueqiao Jin, Lixiang Yan, Zachari Swiecki, Dragan Gašević, Roberto Martinez-Maldonado