JAIR

Understanding AI Trustworthiness: A Scoping Review of AIES & FAccT Articles

理解人工智能可信性：AIES与FAccT文章的综述

Siddharth Mehrotra, Jin Huang, Xuelong Fu, Roel Dobbe, Clara I. Sánchez, Maarten de Rijke

机构 * University of Amsterdam \& Delft University of Technology The Netherlands ； University of Cambridge United Kingdom ； University of Amsterdam The Netherlands ； Delft University of Technology The Netherlands ； University of Amsterdam \& Delft University of Technology ； University of Cambridge ； University of Amsterdam ； Delft University of Technology 纠错

AI总结 本文通过综述AIES和FAccT会议论文，探讨人工智能可信性的概念、测量与验证方法，揭示技术与社会维度的不足，提出跨学科研究的重要性。

Comments Submitted to Journal of Artificial Intelligence Research (JAIR)

Journal ref Journal of Artificial Intelligence Research (2026)

Integrating Column Generation and Large Neighborhood Search for Bus Driver Scheduling with Complex Break Constraints

将列生成与大邻域搜索整合用于具有复杂休息约束的公交司机调度问题

Lucas Kletzander, Tommaso Mannelli Mazzoli, Nysret Musliu, Pascal Van Hentenryck

AI总结 本文提出将列生成与大邻域搜索整合的方法，用于解决具有复杂休息约束的公交司机调度问题，通过改进B&P和LNS方法，提高不同规模实例的求解质量。

Journal ref Journal of Artificial Intelligence Research 85 (2026) 44:1-44:37