arXiv subjects

Jiawei Xie

Publications and source records attributed to Jiawei Xie.

3 recordsLinked to original sources

arXiv2026

An extremal theorem for graphs with non-negative Bakry--Émery curvature

Recently, Chen, Liu, and You (An extremal theorem for positive curvature of graphs, arXiv:2607.02297) proved an extremal theorem for positive Lin--Lu--Yau curvature. They further proposed the similar problems for other discrete curvature. In this paper, we prove a sharp extremal theorem for non-negative Bakry--Émery curvature with non-normalized Laplacian: every graph of order $n\geq 7$ with more than \[ \binom {n}{2}-\lfloor{\frac{n}{2}\rfloor}-2 \] edges satisfies $CD(0,\infty)$, and this threshold is optimal.

math.CO↗

arXiv2025

AI Governance InternationaL Evaluation Index (AGILE Index) 2025

The year 2024 witnessed accelerated global AI governance advancements, marked by strengthened multilateral frameworks and proliferating national regulatory initiatives. This acceleration underscores an unprecedented need to systematically track governance progress--an imperative that drove the launch of the AI Governance InternationaL Evaluation Index (AGILE Index) project since 2023. The inaugural AGILE Index, released in February 2024 after assessing 14 countries, established an operational and comparable baseline framework. Building on pilot insights, AGILE Index 2025 incorporates systematic refinements to better balance scientific rigor with practical adaptability. The updated methodology expands data diversity while enhancing metric validity and cross-national comparability. Reflecting both research advancements and practical policy evolution, AGILE Index 2025 evaluates 40 countries across income levels, regions, and technological development stages, with 4 Pillars, 17 Dimensions and 43 Indicators. In compiling the data, the team integrates multi-source evidence including policy documents, governance practices, research outputs, and risk exposure to construct a unified comparison framework. This approach maps global disparities while enabling countries to identify governance strengths, gaps, and systemic constraints. Through ongoing refinement and iterations, we hope the AGILE Index will fundamentally advance transparency and measurability in global AI governance, delivering data-driven assessments that depict national AI governance capacity, assist governments in recognizing their maturation stages and critical governance issues, and ultimately provide actionable insights for enhancing AI governance systems nationally and globally.

cs.CY↗

arXiv2025

AI Governance InternationaL Evaluation Index (AGILE Index) 2024

The rapid advancement of Artificial Intelligence (AI) technology is profoundly transforming human society and concurrently presenting a series of ethical, legal, and social issues. The effective governance of AI has become a crucial global concern. Since 2022, the extensive deployment of generative AI, particularly large language models, marked a new phase in AI governance. Continuous efforts are being made by the international community in actively addressing the novel challenges posed by these AI developments. As consensus on international governance continues to be established and put into action, the practical importance of conducting a global assessment of the state of AI governance is progressively coming to light. In this context, we initiated the development of the AI Governance InternationaL Evaluation Index (AGILE Index). Adhering to the design principle, "the level of governance should match the level of development," the inaugural evaluation of the AGILE Index commences with an exploration of four foundational pillars: the development level of AI, the AI governance environment, the AI governance instruments, and the AI governance effectiveness. It covers 39 indicators across 18 dimensions to comprehensively assess the AI governance level of 14 representative countries globally. The index is utilized to delve into the status of AI governance to date in 14 countries for the first batch of evaluation. The aim is to depict the current state of AI governance in these countries through data scoring, assist them in identifying their governance stage and uncovering governance issues, and ultimately offer insights for the enhancement of their AI governance systems.

cs.CY↗