Oct 2026· Zenodo (CERN European Organization for Nuclear Research)
Digitalization, Law, and Regulation
Abstract
India's Goods and Services Tax (GST) already runs on algorithms: returns are matched by machine, taxpayers are ranked by risk, and invoices are authenticated through a central portal. Within seven weeks in mid-2026, two High Courts quashed GST proceedings tainted by artificial intelligence (AI), and in doing so raised a question that tax law had not previously needed to answer: who is the decision-maker when a machine has done much of the thinking? This article argues that the answer lies in a familiar principle of administrative law rather than in a new body of 'AI law'. A statutory officer may use an algorithm as evidence or as a drafting aid, but may not allow it to stand in for the application of mind that the statute demands. The article distinguishes predictive analytics from generative drafting tools, shows that the recent decisions address only the second, and warns that a doctrine triggered by visible error will miss competent but unaccountable automation. It proposes an 'algorithm-removal test' and a framework of human-accountable algorithmic taxation to give the principle operational content.
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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With $2.1 million funding from Google.org, the open-source Public Transit Intelligence Hub will unify public transit monitoring, operations, and passenger communication.
