Sep 2026· Zenodo (CERN European Organization for Nuclear Research)
Abstract
This book develops a systematic framework for Artificial Intelligence General Education (AIGE) in response to the cognitive and social transformations of an intelligent society. It identifies cognitive autonomy—the capacity of individuals to actively regulate belief formation, evidence use, trust allocation, the boundaries of judgment and responsibility for action in complex cognitive environments—as a central task of modern general education. Drawing on the scientific foundations of artificial intelligence and the computational transformation of intelligent and social activities, the book explains how AIGE can cultivate four interconnected capabilities: induction, generalization, judgment and self-awareness. It further presents a structured content framework, educational designs spanning primary school through higher education and lifelong learning, and corresponding principles for teaching and assessment. Intended for educators, researchers, policymakers and the wider public, the book provides both a conceptual foundation and a practical framework for advancing Artificial Intelligence General Education in the age of artificial intelligence. NOTE: This is an AI-assisted English translation of Chinese version 2.4. The Chinese edition is authoritative in cases of semantic discrepancy.
GAOKAO-Bench is introduced, an intuitive benchmark that employs questions from the Chinese GAOKAO examination as test samples, including both subjective and objective questions that contribute a robust evaluation benchmark for future large language models and offers valuable insights into the advantages and limitations...
Xiaotian Zhang, Chun-yan Li, Yi Zong et al.· arXiv.org· 216 citations· ⚡17
This work investigates the possibilities of using LLMs in a resume screening setting via a document retrieval framework that simulates job candidate selection and finds that the MTEs are biased, significantly favoring White-associated names in 85% of cases and female-associated names in only 11.1% of cases.
This work shows that orders of magnitude enhancement in performance could be obtained by a combination of hardware improvements and tight quantum-HPC integration and introduces high-performance architectures for quantum-probabilistic computing with custom-designed accelerators to tackle today's industry-scale classical...
Masoud Mohseni, Artur Scherer, K. Johnson et al.· arXiv.org· 121 citations· ⚡9
This paper presents a comprehensive overview of the Ultralytics YOLO family, emphasizing architectural evolution, benchmarking, deployment, and emerging directions from YOLOv5 through YOLO27, and examines detection, segmentation, depth, classification, pose, oriented detection, tracking, export, quantization, and deplo...
This work revisits schema linking when using the latest generation of large language models (LLMs) and finds empirically that newer models are adept at utilizing relevant schema elements during generation even in the presence of large numbers of irrelevant ones.
Karime Maamari, Fadhil Abubaker, Daniel Jaroslawicz et al.· arXiv.org· 109 citations· ⚡19
A novel threat is unveiled in which attackers steer the RAG system's response by injecting malicious passages into its knowledge base, enabling the attacker to steer the response without altering the user input or modifying the RAG weights.
Jiaqi Xue, Meng Zheng, Yebowen Hu et al.· arXiv.org· 109 citations· ⚡8
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