Scientific discovery in the age of artificial intelligence

H Wang, T Fu, Y Du, W Gao, K Huang, Z Liu… - Nature, 2023 - nature.com
Artificial intelligence (AI) is being increasingly integrated into scientific discovery to augment
and accelerate research, helping scientists to generate hypotheses, design experiments …

Survey of explainable AI techniques in healthcare

A Chaddad, J Peng, J Xu, A Bouridane - Sensors, 2023 - mdpi.com
Artificial intelligence (AI) with deep learning models has been widely applied in numerous
domains, including medical imaging and healthcare tasks. In the medical field, any judgment …

[HTML][HTML] Explainable Artificial Intelligence (XAI): What we know and what is left to attain Trustworthy Artificial Intelligence

S Ali, T Abuhmed, S El-Sappagh, K Muhammad… - Information fusion, 2023 - Elsevier
Artificial intelligence (AI) is currently being utilized in a wide range of sophisticated
applications, but the outcomes of many AI models are challenging to comprehend and trust …

Trustworthy llms: a survey and guideline for evaluating large language models' alignment

Y Liu, Y Yao, JF Ton, X Zhang, R Guo, H Cheng… - arXiv preprint arXiv …, 2023 - arxiv.org
Ensuring alignment, which refers to making models behave in accordance with human
intentions [1, 2], has become a critical task before deploying large language models (LLMs) …

Explainability for large language models: A survey

H Zhao, H Chen, F Yang, N Liu, H Deng, H Cai… - ACM Transactions on …, 2024 - dl.acm.org
Large language models (LLMs) have demonstrated impressive capabilities in natural
language processing. However, their internal mechanisms are still unclear and this lack of …

Trustworthy artificial intelligence: a review

D Kaur, S Uslu, KJ Rittichier, A Durresi - ACM computing surveys (CSUR …, 2022 - dl.acm.org
Artificial intelligence (AI) and algorithmic decision making are having a profound impact on
our daily lives. These systems are vastly used in different high-stakes applications like …

Interpreting black-box models: a review on explainable artificial intelligence

V Hassija, V Chamola, A Mahapatra, A Singal… - Cognitive …, 2024 - Springer
Recent years have seen a tremendous growth in Artificial Intelligence (AI)-based
methodological development in a broad range of domains. In this rapidly evolving field …

A review of taxonomies of explainable artificial intelligence (XAI) methods

T Speith - Proceedings of the 2022 ACM conference on fairness …, 2022 - dl.acm.org
The recent surge in publications related to explainable artificial intelligence (XAI) has led to
an almost insurmountable wall if one wants to get started or stay up to date with XAI. For this …

From attribution maps to human-understandable explanations through concept relevance propagation

R Achtibat, M Dreyer, I Eisenbraun, S Bosse… - Nature Machine …, 2023 - nature.com
The field of explainable artificial intelligence (XAI) aims to bring transparency to today's
powerful but opaque deep learning models. While local XAI methods explain individual …

From anecdotal evidence to quantitative evaluation methods: A systematic review on evaluating explainable ai

M Nauta, J Trienes, S Pathak, E Nguyen… - ACM Computing …, 2023 - dl.acm.org
The rising popularity of explainable artificial intelligence (XAI) to understand high-performing
black boxes raised the question of how to evaluate explanations of machine learning (ML) …