Software testing with large language models: Survey, landscape, and vision
Pre-trained large language models (LLMs) have recently emerged as a breakthrough
technology in natural language processing and artificial intelligence, with the ability to …
technology in natural language processing and artificial intelligence, with the ability to …
Bias mitigation for machine learning classifiers: A comprehensive survey
This article provides a comprehensive survey of bias mitigation methods for achieving
fairness in Machine Learning (ML) models. We collect a total of 341 publications concerning …
fairness in Machine Learning (ML) models. We collect a total of 341 publications concerning …
“Everyone wants to do the model work, not the data work”: Data Cascades in High-Stakes AI
AI models are increasingly applied in high-stakes domains like health and conservation.
Data quality carries an elevated significance in high-stakes AI due to its heightened …
Data quality carries an elevated significance in high-stakes AI due to its heightened …
[BOOK][B] Human-centered AI
B Shneiderman - 2022 - books.google.com
The remarkable progress in algorithms for machine and deep learning have opened the
doors to new opportunities, and some dark possibilities. However, a bright future awaits …
doors to new opportunities, and some dark possibilities. However, a bright future awaits …
Bridging the gap between ethics and practice: guidelines for reliable, safe, and trustworthy human-centered AI systems
B Shneiderman - ACM Transactions on Interactive Intelligent Systems …, 2020 - dl.acm.org
This article attempts to bridge the gap between widely discussed ethical principles of Human-
centered AI (HCAI) and practical steps for effective governance. Since HCAI systems are …
centered AI (HCAI) and practical steps for effective governance. Since HCAI systems are …
Dawn of the transformer era in speech emotion recognition: closing the valence gap
Recent advances in transformer-based architectures have shown promise in several
machine learning tasks. In the audio domain, such architectures have been successfully …
machine learning tasks. In the audio domain, such architectures have been successfully …
Trustworthy AI: From principles to practices
The rapid development of Artificial Intelligence (AI) technology has enabled the deployment
of various systems based on it. However, many current AI systems are found vulnerable to …
of various systems based on it. However, many current AI systems are found vulnerable to …
Software engineering for AI-based systems: a survey
AI-based systems are software systems with functionalities enabled by at least one AI
component (eg, for image-, speech-recognition, and autonomous driving). AI-based systems …
component (eg, for image-, speech-recognition, and autonomous driving). AI-based systems …
Unsupervised translation of programming languages
A transcompiler, also known as source-to-source translator, is a system that converts source
code from a high-level programming language (such as C++ or Python) to another …
code from a high-level programming language (such as C++ or Python) to another …
Testing machine learning based systems: a systematic map**
Abstract Context: A Machine Learning based System (MLS) is a software system including
one or more components that learn how to perform a task from a given data set. The …
one or more components that learn how to perform a task from a given data set. The …