Lost in Vagueness: Towards Context-Sensitive Standards for Robustness Assessment under the EU AI Act | Paper Citation Record

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Lost in Vagueness: Towards Context-Sensitive Standards for Robustness Assessment under the EU AI Act Unresolved cited work

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This paper cites Capai-a procedure for conducting conformity assessment of ai systems in line with the eu artificial intelligence act.Available at SSRN 4064091, 2022.

Lost in Vagueness: Towards Context-Sensitive Standards for Robustness Assessment under the EU AI Act Capai-a procedure for conducting conformity assessment of ai systems in line with the eu artificial intelligence act.Available at SSRN 4064091, 2022

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This paper cites Harmonised standards for the european ai act.

Lost in Vagueness: Towards Context-Sensitive Standards for Robustness Assessment under the EU AI Act Harmonised standards for the european ai act

Reference 4

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This paper cites Beyond generalization: a theory of robustness in machine learning.Synthese, 202(109), 2023.

Lost in Vagueness: Towards Context-Sensitive Standards for Robustness Assessment under the EU AI Act Beyond generalization: a theory of robustness in machine learning.Synthese, 202(109), 2023

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This paper cites Artificial intelligence (AI)—assessment of the robustness of neural networks — part 1: Overview (iso/iec tr 24029-1:2021).

Lost in Vagueness: Towards Context-Sensitive Standards for Robustness Assessment under the EU AI Act Artificial intelligence (AI)—assessment of the robustness of neural networks — part 1: Overview (iso/iec tr 24029-1:2021)

Reference 6

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This paper cites About the joint technical committee, 2025.

Lost in Vagueness: Towards Context-Sensitive Standards for Robustness Assessment under the EU AI Act About the joint technical committee, 2025

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Lost in Vagueness: Towards Context-Sensitive Standards for Robustness Assessment under the EU AI Act Unresolved cited work

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This paper cites AI robustness: a human-centered perspective on technological challenges and opportunities.ACM Computing Surveys, 57(6):1–38, 2025.

Lost in Vagueness: Towards Context-Sensitive Standards for Robustness Assessment under the EU AI Act AI robustness: a human-centered perspective on technological challenges and opportunities.ACM Computing Surveys, 57(6):1–38, 2025

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This paper cites On robustness: An undervalued dimension of human rationality.

Lost in Vagueness: Towards Context-Sensitive Standards for Robustness Assessment under the EU AI Act On robustness: An undervalued dimension of human rationality

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This paper cites A systematic review of robustness in deep learning for computer vision: Mind the gap?, 2021.

Lost in Vagueness: Towards Context-Sensitive Standards for Robustness Assessment under the EU AI Act A systematic review of robustness in deep learning for computer vision: Mind the gap?, 2021

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This paper cites Assessing robustness of text classification through maximal safe radius com- putation.

Lost in Vagueness: Towards Context-Sensitive Standards for Robustness Assessment under the EU AI Act Assessing robustness of text classification through maximal safe radius com- putation

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This paper cites The many faces of robustness: A critical analysis of out-of- distribution generalization.2021 IEEE/CVF International Conference on Computer Vision (ICCV), pages 8320–8329, 2020.

Lost in Vagueness: Towards Context-Sensitive Standards for Robustness Assessment under the EU AI Act The many faces of robustness: A critical analysis of out-of- distribution generalization.2021 IEEE/CVF International Conference on Computer Vision (ICCV), pages 8320–8329, 2020

Reference 13

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This paper cites Software engineering — systems and software quality requirements and evaluation (SQuaRE) — quality model for AI system.

Lost in Vagueness: Towards Context-Sensitive Standards for Robustness Assessment under the EU AI Act Software engineering — systems and software quality requirements and evaluation (SQuaRE) — quality model for AI system

Reference 14

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Lost in Vagueness: Towards Context-Sensitive Standards for Robustness Assessment under the EU AI Act O’Reilly Media, Inc

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This paper cites Simon and Schuster, 2021.

Lost in Vagueness: Towards Context-Sensitive Standards for Robustness Assessment under the EU AI Act Simon and Schuster, 2021

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This paper cites A scoping review of robustness concepts for machine learning in healthcare.npj Digital Medicine, 8(1):38, 2025.

Lost in Vagueness: Towards Context-Sensitive Standards for Robustness Assessment under the EU AI Act A scoping review of robustness concepts for machine learning in healthcare.npj Digital Medicine, 8(1):38, 2025

Reference 17

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This paper cites Dataset shift in machine learning.

Lost in Vagueness: Towards Context-Sensitive Standards for Robustness Assessment under the EU AI Act Dataset shift in machine learning

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This paper cites Data Quality Matters For Adversarial Training: An Empirical Study.

Lost in Vagueness: Towards Context-Sensitive Standards for Robustness Assessment under the EU AI Act Data Quality Matters For Adversarial Training: An Empirical Study

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This paper cites Robustness in deep learning models for medical diagnostics: security and adversarial challenges towards robust AI applications.

Lost in Vagueness: Towards Context-Sensitive Standards for Robustness Assessment under the EU AI Act Robustness in deep learning models for medical diagnostics: security and adversarial challenges towards robust AI applications

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This paper cites Benchmarking robustness of multimodal image-text models under distribution shift, 2022.

Lost in Vagueness: Towards Context-Sensitive Standards for Robustness Assessment under the EU AI Act Benchmarking robustness of multimodal image-text models under distribution shift, 2022

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Lost in Vagueness: Towards Context-Sensitive Standards for Robustness Assessment under the EU AI Act Manning, Prabhakar Raghavan, and Hinrich Schütze

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Lost in Vagueness: Towards Context-Sensitive Standards for Robustness Assessment under the EU AI Act Architecture selection via the trade-off between accuracy and robustness, 2019

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Lost in Vagueness: Towards Context-Sensitive Standards for Robustness Assessment under the EU AI Act Robustness may be at odds with accuracy

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Lost in Vagueness: Towards Context-Sensitive Standards for Robustness Assessment under the EU AI Act Impact of architectural modifications on deep learning adversarial robustness

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Lost in Vagueness: Towards Context-Sensitive Standards for Robustness Assessment under the EU AI Act Buelow, Rupert Langer, Bastian Dislich, Peter Boor, V olkmar Schulz, and Jakob Nikolas Kather

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This paper cites Hyperpa- rameter optimization for deep neural network models: a comprehensive study on methods and techniques.Innovations in Systems and Software Engineering, pages 1–12, 2023.

Lost in Vagueness: Towards Context-Sensitive Standards for Robustness Assessment under the EU AI Act Hyperpa- rameter optimization for deep neural network models: a comprehensive study on methods and techniques.Innovations in Systems and Software Engineering, pages 1–12, 2023

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Lost in Vagueness: Towards Context-Sensitive Standards for Robustness Assessment under the EU AI Act The role of hyperparameters in machine learning models and how to tune them.Political Science Research and Methods, 12(4):841–848, 2024

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Lost in Vagueness: Towards Context-Sensitive Standards for Robustness Assessment under the EU AI Act Machine learning robustness: A primer

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Lost in Vagueness: Towards Context-Sensitive Standards for Robustness Assessment under the EU AI Act Graph robustness benchmark: Benchmarking the adversarial robustness of graph machine learning

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Lost in Vagueness: Towards Context-Sensitive Standards for Robustness Assessment under the EU AI Act Intriguing properties of neural networks

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Lost in Vagueness: Towards Context-Sensitive Standards for Robustness Assessment under the EU AI Act Wilds: A benchmark of in-the-wild distribution shifts

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Lost in Vagueness: Towards Context-Sensitive Standards for Robustness Assessment under the EU AI Act Structural robustness for deep learning architectures

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Lost in Vagueness: Towards Context-Sensitive Standards for Robustness Assessment under the EU AI Act Generative adversarial nets.Advances in neural information processing systems, 27, 2014

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Lost in Vagueness: Towards Context-Sensitive Standards for Robustness Assessment under the EU AI Act Deeptest: Automated testing of deep- neural-network-driven autonomous cars

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Lost in Vagueness: Towards Context-Sensitive Standards for Robustness Assessment under the EU AI Act Metamorphic testing of driverless cars.Communications of the ACM, 62(3):61–67, 2019

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Lost in Vagueness: Towards Context-Sensitive Standards for Robustness Assessment under the EU AI Act MuNN: Mutation analysis of neural networks

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Lost in Vagueness: Towards Context-Sensitive Standards for Robustness Assessment under the EU AI Act Deepmutation: Mutation testing of deep learning systems

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Lost in Vagueness: Towards Context-Sensitive Standards for Robustness Assessment under the EU AI Act Robustbench: a standardized adversarial robustness benchmark

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Lost in Vagueness: Towards Context-Sensitive Standards for Robustness Assessment under the EU AI Act Openai gym, 2016

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Lost in Vagueness: Towards Context-Sensitive Standards for Robustness Assessment under the EU AI Act IOHprofiler: A Benchmarking and Profiling Tool for Iterative Optimization Heuristics

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Lost in Vagueness: Towards Context-Sensitive Standards for Robustness Assessment under the EU AI Act Iohanalyzer: Detailed performance analyses for iterative optimization heuristics.ACM Transactions on Evolutionary Learning and Optimization, 2(1):1–29, 2022

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Lost in Vagueness: Towards Context-Sensitive Standards for Robustness Assessment under the EU AI Act Deep learning for auto- mated classification of tuberculosis-related chest x-ray: dataset distribution shift limits diagnos- tic performance generalizability.Heliyon, 6(8), 2020

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Lost in Vagueness: Towards Context-Sensitive Standards for Robustness Assessment under the EU AI Act Medfuzz: Exploring the robustness of large language models in medical question answering, 2024

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Lost in Vagueness: Towards Context-Sensitive Standards for Robustness Assessment under the EU AI Act Standard setting overview | eu artificial intelligence act, 2025

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Lost in Vagueness: Towards Context-Sensitive Standards for Robustness Assessment under the EU AI Act Framing governance for a contested emerging technology: insights from ai policy.Policy and Society, 40(2):158–177, 2021

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Lost in Vagueness: Towards Context-Sensitive Standards for Robustness Assessment under the EU AI Act Navigating the ai revolution: the case for precise regulation in health care

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Lost in Vagueness: Towards Context-Sensitive Standards for Robustness Assessment under the EU AI Act Too broad to handle: can we" fix" harmonised standards on artificial intelli- gence by focusing on vertical sectors?, 2024

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Lost in Vagueness: Towards Context-Sensitive Standards for Robustness Assessment under the EU AI Act Machado, Christopher Burr, Josh Cowls, Indra Joshi, Mariarosaria Taddeo, and Luciano Floridi

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Lost in Vagueness: Towards Context-Sensitive Standards for Robustness Assessment under the EU AI Act Edicoes Loyola, 1994

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Lost in Vagueness: Towards Context-Sensitive Standards for Robustness Assessment under the EU AI Act Analysis of the preliminary ai standardisation work plan in support of the ai act

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Lost in Vagueness: Towards Context-Sensitive Standards for Robustness Assessment under the EU AI Act Ai hazard management: A framework for the systematic management of root causes for ai risks

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Lost in Vagueness: Towards Context-Sensitive Standards for Robustness Assessment under the EU AI Act Unresolved cited work

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Lost in Vagueness: Towards Context-Sensitive Standards for Robustness Assessment under the EU AI Act Artificial intelligence measurement and evaluation at the national institute of standards and technology.National Institute of Standards and Technology, 2021

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Observation 02413e32-e011-470d-a071-c4e63d72701a · outbound

This paper cites Why rankings of biomedical image analysis competitions should be interpreted with care.Nature communications, 9(1):5217, 2018.

Lost in Vagueness: Towards Context-Sensitive Standards for Robustness Assessment under the EU AI Act Why rankings of biomedical image analysis competitions should be interpreted with care.Nature communications, 9(1):5217, 2018

Reference 55

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Observation 4e59f95a-fbb2-4f21-84fd-222e4a1fd209 · outbound

This paper cites Toward an evaluation science for generative ai systems, 2025.

Lost in Vagueness: Towards Context-Sensitive Standards for Robustness Assessment under the EU AI Act Toward an evaluation science for generative ai systems, 2025

Reference 56

Resolution: unresolved; no resolver link, observed 2026-08-03T21:23:49.310103Z

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Observation 0320776c-5132-422d-b31f-7f4a74f634ab · outbound

This paper cites Artificial intelligence act and regulatory sandboxes.European Parliamentary Research Service, 6, 2022.

Lost in Vagueness: Towards Context-Sensitive Standards for Robustness Assessment under the EU AI Act Artificial intelligence act and regulatory sandboxes.European Parliamentary Research Service, 6, 2022

Reference 57

Resolution: unresolved; no resolver link, observed 2026-08-03T21:23:49.467684Z

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Observation 70a9564d-ed82-44a0-84cd-84d94dfc428e · outbound

This paper cites Due, Hira Shah, Thiago Moraes, Nathan Genicot, and Martin Canter.

Lost in Vagueness: Towards Context-Sensitive Standards for Robustness Assessment under the EU AI Act Due, Hira Shah, Thiago Moraes, Nathan Genicot, and Martin Canter

Reference 58

Resolution: unresolved; no resolver link, observed 2026-08-03T21:23:49.590638Z

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