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
ActionReasoningBench: Reasoning about Actions with and without Ramification Constraints
Divij Handa, Pavel Dolin, Shrinidhi Kumbhar, Tran Cao Son, Chitta Baral
Are Large Language Models the New Interface for Data Pipelines?
Sylvio Barbon Junior, Paolo Ceravolo, Sven Groppe, Mustafa Jarrar, Samira Maghool, Florence Sèdes, Soror Sahri, Maurice Van Keulen
Logic-Based Explainability: Past, Present & Future
Joao Marques-Silva
Investigating the Potential of Using Large Language Models for Scheduling
Deddy Jobson, Yilin Li
A Toolbox for Supporting Research on AI in Water Distribution Networks
André Artelt, Marios S. Kyriakou, Stelios G. Vrachimis, Demetrios G. Eliades, Barbara Hammer, Marios M. Polycarpou
I've got the "Answer"! Interpretation of LLMs Hidden States in Question Answering
Valeriya Goloviznina, Evgeny Kotelnikov
Comparative Analysis Vision of Worldwide AI Courses
Jianing Xia, Man Li, Jianxin Li
AI Agents Under Threat: A Survey of Key Security Challenges and Future Pathways
Zehang Deng, Yongjian Guo, Changzhou Han, Wanlun Ma, Junwu Xiong, Sheng Wen, Yang Xiang
An approximation-based approach versus an AI one for the study of CT images of abdominal aorta aneurysms
Lucrezia Rinelli, Arianna Travaglini, Nicolò Vescera, Gianluca Vinti
Position: Cracking the Code of Cascading Disparity Towards Marginalized Communities
Golnoosh Farnadi, Mohammad Havaei, Negar Rostamzadeh
Evolutionary Computation for the Design and Enrichment of General-Purpose Artificial Intelligence Systems: Survey and Prospects
Javier Poyatos, Javier Del Ser, Salvador Garcia, Hisao Ishibuchi, Daniel Molina, Isaac Triguero, Bing Xue, Xin Yao, Francisco Herrera
Problematizing AI Omnipresence in Landscape Architecture
Phillip Fernberg, Zihao Zhang
Position: An Inner Interpretability Framework for AI Inspired by Lessons from Cognitive Neuroscience
Martina G. Vilas, Federico Adolfi, David Poeppel, Gemma Roig
Using Artificial Intelligence to Accelerate Collective Intelligence: Policy Synth and Smarter Crowdsourcing
Róbert Bjarnason, Dane Gambrell, Joshua Lanthier-Welch
How Ethical Should AI Be? How AI Alignment Shapes the Risk Preferences of LLMs
Shumiao Ouyang, Hayong Yun, Xingjian Zheng
Harvard Undergraduate Survey on Generative AI
Shikoh Hirabayashi, Rishab Jain, Nikola Jurković, Gabriel Wu
The Embodied World Model Based on LLM with Visual Information and Prediction-Oriented Prompts
Wakana Haijima, Kou Nakakubo, Masahiro Suzuki, Yutaka Matsuo
Learning to Play 7 Wonders Duel Without Human Supervision
Giovanni Paolini, Lorenzo Moreschini, Francesco Veneziano, Alessandro Iraci
Discovering an interpretable mathematical expression for a full wind-turbine wake with artificial intelligence enhanced symbolic regression
Ding Wang, Yuntian Chen, Shiyi Chen