中文
相关论文

相关论文: Lost in Vagueness: Towards Context-Sensitive Stand…

200 篇论文

The EU Artificial Intelligence Act (AIA) establishes different legal principles for different types of AI systems. While prior work has sought to clarify some of these principles, little attention has been paid to robustness and…

人工智能 · 计算机科学 2025-05-29 Henrik Nolte , Miriam Rateike , Michèle Finck

Despite the impressive performance of Artificial Intelligence (AI) systems, their robustness remains elusive and constitutes a key issue that impedes large-scale adoption. Robustness has been studied in many domains of AI, yet with…

人工智能 · 计算机科学 2022-10-20 Andrea Tocchetti , Lorenzo Corti , Agathe Balayn , Mireia Yurrita , Philip Lippmann , Marco Brambilla , Jie Yang

The European Union's Artificial Intelligence (AI) Act defines robustness, resilience, and security requirements for high-risk sectors but lacks detailed methodologies for assessment. This paper introduces a novel framework for…

人工智能 · 计算机科学 2025-04-21 Timothy Tjhay , Ricardo J. Bessa , Jose Paulos

This white paper examines the technical foundations of European AI standardization under the AI Act. It explains how harmonized standards enable the presumption of conformity mechanism, describes the CEN/CENELEC standardization process, and…

计算机与社会 · 计算机科学 2026-02-03 Piercosma Bisconti , Marcello Galisai

Technical and legal debates frequently suggest that "accuracy" is an objective, measurable, and purely technical property. We challenge this view, showing that evaluating AI performance fundamentally depends on context-dependent normative…

AI-based robots and vehicles are expected to operate safely in complex and dynamic environments, even in the presence of component degradation. In such systems, perception relies on sensors such as cameras to capture environmental data,…

Assured AI in unrestricted settings is a critical problem. Our framework addresses AI assurance challenges lying at the intersection of domain adaptation, fairness, and counterfactuals analysis, operating via the discovery and intervention…

机器学习 · 计算机科学 2021-11-19 William Paul , Philippe Burlina

Algorithmic robustness refers to the sustained performance of a computational system in the face of change in the nature of the environment in which that system operates or in the task that the system is meant to perform. Below, we motivate…

人工智能 · 计算机科学 2023-11-14 David Jensen , Brian LaMacchia , Ufuk Topcu , Pamela Wisniewski

We tackle here a specific, still not widely addressed aspect, of AI robustness, which consists of seeking invariance / insensitivity of model performance to hidden factors of variations in the data. Towards this end, we employ a two step…

机器学习 · 计算机科学 2022-03-04 William Paul , Philippe Burlina

Large language models are prone to misuse and vulnerable to security threats, raising significant safety and security concerns. The European Union's Artificial Intelligence Act seeks to enforce AI robustness in certain contexts, but faces…

密码学与安全 · 计算机科学 2024-10-10 Tomas Bueno Momcilovic , Beat Buesser , Giulio Zizzo , Mark Purcell , Dian Balta

The Robust Artificial Intelligence System Assurance (RAISA) workshop will focus on research, development and application of robust artificial intelligence (AI) and machine learning (ML) systems. Rather than studying robustness with respect…

人工智能 · 计算机科学 2022-02-11 Olivia Brown , Brad Dillman

This chapter explores the foundational concept of robustness in Machine Learning (ML) and its integral role in establishing trustworthiness in Artificial Intelligence (AI) systems. The discussion begins with a detailed definition of…

机器学习 · 计算机科学 2024-05-07 Houssem Ben Braiek , Foutse Khomh

In December 2023, the European Parliament provisionally agreed on the EU AI Act. This unprecedented regulatory framework for AI systems lays out guidelines to ensure the safety, legality, and trustworthiness of AI products. This paper…

人工智能 · 计算机科学 2024-07-12 J. Kelly , S. Zafar , L. Heidemann , J. Zacchi , D. Espinoza , N. Mata

This position paper contends that modern AI research must adopt an antifragile perspective on safety -- one in which the system's capacity to guarantee long-term AI safety such as handling rare or out-of-distribution (OOD) events expands…

人工智能 · 计算机科学 2025-09-18 Ming Jin , Hyunin Lee

With the advancements in machine learning (ML) methods and compute resources, artificial intelligence (AI) empowered systems are becoming a prevailing technology. However, current AI technology such as deep learning is not flawless. The…

机器学习 · 计算机科学 2023-01-10 Pin-Yu Chen , Payel Das

In the last years, AI systems, in particular neural networks, have seen a tremendous increase in performance, and they are now used in a broad range of applications. Unlike classical symbolic AI systems, neural networks are trained using…

计算机视觉与模式识别 · 计算机科学 2021-08-16 Christian Berghoff , Pavol Bielik , Matthias Neu , Petar Tsankov , Arndt von Twickel

With the upcoming enforcement of the EU AI Act, documentation of high-risk AI systems and their risk management information will become a legal requirement playing a pivotal role in demonstration of compliance. Despite its importance, there…

The many initiatives on trustworthy AI result in a confusing and multipolar landscape that organizations operating within the fluid and complex international value chains must navigate in pursuing trustworthy AI. The EU's AI Act will now…

人工智能 · 计算机科学 2024-08-23 Julio Hernandez , Delaram Golpayegani , Dave Lewis

The authors are concerned about the safety, health, and rights of the European citizens due to inadequate measures and procedures required by the current draft of the EU Artificial Intelligence (AI) Act for the conformity assessment of AI…

机器学习 · 统计学 2023-10-05 Bernhard Nessler , Thomas Doms , Sepp Hochreiter

In recent years, there has been significant attention given to the robustness assessment of neural networks. Robustness plays a critical role in ensuring reliable operation of artificial intelligence (AI) systems in complex and uncertain…

计算机视觉与模式识别 · 计算机科学 2024-04-16 Jie Wang , Jun Ai , Minyan Lu , Haoran Su , Dan Yu , Yutao Zhang , Junda Zhu , Jingyu Liu
‹ 上一页 1 2 3 10 下一页 ›