Oct 2026· RSF Conference Series Business Management and Social Sciences
International Relations and Foreign Policy
Abstract
The rapid convergence of artificial intelligence, big data, and global digital platforms has fundamentally altered diplomatic practice, shifting it from closed, state-centric negotiation to real-time, data-driven, and algorithmically mediated interaction. Existing international relations theory, built around linear and deterministic assumptions about state behavior, increasingly struggles to explain the non-linear, probabilistic dynamics of contemporary diplomatic practice. This paper introduces quantum diplomacy as an analytical metaphor - borrowed from quantum physics rather than asserting any literal quantum-mechanical process - and develops the Quantum Diplomacy Transformation Framework (QDTF) as a new conceptual model for analyzing diplomacy in the digital era. The study employs a qualitative conceptual research design based on systematic document analysis, synthesizing digital power theory, complex adaptive systems theory, and algorithmic governance theory drawn from peer-reviewed literature and policy documents published between 2011 and 2025. The analysis identifies four defining characteristics of quantum diplomacy - real-time decision-making, non-linear causality, algorithmic mediation, and process invisibility - integrated into a five-layer QDTF model linking technological infrastructure, hybrid actors, data-driven mechanisms, and geopolitical outcomes. Unlike earlier digital diplomacy scholarship, which centers on the tools diplomats use, QDTF theorizes the causal logic connecting these tools to diplomatic outcomes. Applied illustratively to Indonesia, the framework shows a paradoxical position of large digital potential constrained by regulatory and infrastructural gaps. The paper contributes a new theoretical vocabulary, five testable propositions, and an analytical foundation for future empirical testing and evidence-based policy design.
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
With $2.1 million funding from Google.org, the open-source Public Transit Intelligence Hub will unify public transit monitoring, operations, and passenger communication.
Professor Sherry Turkle’s new book, “Artificial Intimacy,” offers a withering critique of chatbots and the antisocial dynamics she believes they encourage.
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.