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
opp/ai: Optimistic Privacy-Preserving AI on Blockchain
Cathie So, KD Conway, Xiaohang Yu, Suning Yao, Kartin Wong
Demographic Bias of Expert-Level Vision-Language Foundation Models in Medical Imaging
Yuzhe Yang, Yujia Liu, Xin Liu, Avanti Gulhane, Domenico Mastrodicasa, Wei Wu, Edward J Wang, Dushyant W Sahani, Shwetak Patel
The European Commitment to Human-Centered Technology: The Integral Role of HCI in the EU AI Act's Success
André Calero Valdez, Moreen Heine, Thomas Franke, Nicole Jochems, Hans-Christian Jetter, Tim Schrills
Unleashing the Power of AI. A Systematic Review of Cutting-Edge Techniques in AI-Enhanced Scientometrics, Webometrics, and Bibliometrics
Hamid Reza Saeidnia, Elaheh Hosseini, Shadi Abdoli, Marcel Ausloos
Automating Psychological Hypothesis Generation with AI: Large Language Models Meet Causal Graph
Song Tong, Kai Mao, Zhen Huang, Yukun Zhao, Kaiping Peng
Vision-Language Navigation with Embodied Intelligence: A Survey
Peng Gao, Peng Wang, Feng Gao, Fei Wang, Ruyue Yuan
Exploring ChatGPT and its Impact on Society
Md. Asraful Haque, Shuai Li
Testing autonomous vehicles and AI: perspectives and challenges from cybersecurity, transparency, robustness and fairness
David Fernández Llorca, Ronan Hamon, Henrik Junklewitz, Kathrin Grosse, Lars Kunze, Patrick Seiniger, Robert Swaim, Nick Reed, Alexandre Alahi, Emilia Gómez, Ignacio Sánchez, Akos Kriston
Mastering the Game of Guandan with Deep Reinforcement Learning and Behavior Regulating
Yifan Yanggong, Hao Pan, Lei Wang
A Literature Review of Literature Reviews in Pattern Analysis and Machine Intelligence
Penghai Zhao, Xin Zhang, Ming-Ming Cheng, Jian Yang, Xiang Li
From Cloud to Edge: Rethinking Generative AI for Low-Resource Design Challenges
Sai Krishna Revanth Vuruma, Ashley Margetts, Jianhai Su, Faez Ahmed, Biplav Srivastava
CHATATC: Large Language Model-Driven Conversational Agents for Supporting Strategic Air Traffic Flow Management
Sinan Abdulhak, Wayne Hubbard, Karthik Gopalakrishnan, Max Z. Li
Evolving AI Collectives to Enhance Human Diversity and Enable Self-Regulation
Shiyang Lai, Yujin Potter, Junsol Kim, Richard Zhuang, Dawn Song, James Evans
AI Sustainability in Practice Part Two: Sustainability Throughout the AI Workflow
David Leslie, Cami Rincon, Morgan Briggs, Antonella Perini, Smera Jayadeva, Ann Borda, SJ Bennett, Christopher Burr, Mhairi Aitken, Michael Katell, Claudia Fischer, Janis Wong, Ismael Kherroubi Garcia
Grounding from an AI and Cognitive Science Lens
Goonmeet Bajaj, Srinivasan Parthasarathy, Valerie L. Shalin, Amit Sheth
A real-time Artificial Intelligence system for learning Sign Language
Elisa Cabana
Offline Training of Language Model Agents with Functions as Learnable Weights
Shaokun Zhang, Jieyu Zhang, Jiale Liu, Linxin Song, Chi Wang, Ranjay Krishna, Qingyun Wu
Multi-Generative Agent Collective Decision-Making in Urban Planning: A Case Study for Kendall Square Renovation
Jin Gao, Hanyong Xu, Luc Dao
Enhancing Surgical Performance in Cardiothoracic Surgery with Innovations from Computer Vision and Artificial Intelligence: A Narrative Review
Merryn D. Constable, Hubert P. H. Shum, Stephen Clark