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Opening the Software Engineering Toolbox for the Assessment of
  Trustworthy AI
v1v2 (latest)

Opening the Software Engineering Toolbox for the Assessment of Trustworthy AI

14 July 2020
M. K. Ahuja
M. Belaid
Pierre Bernabé
Mathieu Collet
A. Gotlieb
Chhagan Lal
D. Marijan
S. Sen
Aizaz Sharif
Helge Spieker
ArXiv (abs)PDFHTML

Papers citing "Opening the Software Engineering Toolbox for the Assessment of Trustworthy AI"

5 / 5 papers shown
Mapping the Trust Terrain: LLMs in Software Engineering -- Insights and Perspectives
Mapping the Trust Terrain: LLMs in Software Engineering -- Insights and Perspectives
Dipin Khati
Yijin Liu
David Nader-Palacio
Yixuan Zhang
Denys Poshyvanyk
365
2
0
18 Mar 2025
Towards More Trustworthy and Interpretable LLMs for Code through
  Syntax-Grounded Explanations
Towards More Trustworthy and Interpretable LLMs for Code through Syntax-Grounded Explanations
David Nader-Palacio
Daniel Rodríguez-Cárdenas
Alejandro Velasco
Dipin Khati
Kevin Moran
Denys Poshyvanyk
406
13
0
12 Jul 2024
Responsible AI Pattern Catalogue: A Collection of Best Practices for AI
  Governance and Engineering
Responsible AI Pattern Catalogue: A Collection of Best Practices for AI Governance and EngineeringACM Computing Surveys (ACM CSUR), 2022
Qinghua Lu
Liming Zhu
Xiwei Xu
Jon Whittle
Didar Zowghi
Aurelie Jacquet
AI4TS
487
105
0
12 Sep 2022
Towards a Roadmap on Software Engineering for Responsible AI
Towards a Roadmap on Software Engineering for Responsible AI
Qinghua Lu
Liming Zhu
Xiwei Xu
Jon Whittle
Zhenchang Xing
258
75
0
09 Mar 2022
A Software Engineering Perspective on Engineering Machine Learning
  Systems: State of the Art and Challenges
A Software Engineering Perspective on Engineering Machine Learning Systems: State of the Art and ChallengesJournal of Systems and Software (JSS), 2020
G. Giray
420
164
0
14 Dec 2020
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