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 …

Chatgpt and open-ai models: A preliminary review

KI Roumeliotis, ND Tselikas - Future Internet, 2023‏ - mdpi.com
According to numerous reports, ChatGPT represents a significant breakthrough in the field of
artificial intelligence. ChatGPT is a pre-trained AI model designed to engage in natural …

[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 …

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 …

Kan: Kolmogorov-arnold networks

Z Liu, Y Wang, S Vaidya, F Ruehle, J Halverson… - arxiv preprint arxiv …, 2024‏ - arxiv.org
Inspired by the Kolmogorov-Arnold representation theorem, we propose Kolmogorov-Arnold
Networks (KANs) as promising alternatives to Multi-Layer Perceptrons (MLPs). While MLPs …

Language models don't always say what they think: Unfaithful explanations in chain-of-thought prompting

M Turpin, J Michael, E Perez… - Advances in Neural …, 2023‏ - proceedings.neurips.cc
Abstract Large Language Models (LLMs) can achieve strong performance on many tasks by
producing step-by-step reasoning before giving a final output, often referred to as chain-of …

Re-thinking data strategy and integration for artificial intelligence: concepts, opportunities, and challenges

A Aldoseri, KN Al-Khalifa, AM Hamouda - Applied Sciences, 2023‏ - mdpi.com
The use of artificial intelligence (AI) is becoming more prevalent across industries such as
healthcare, finance, and transportation. Artificial intelligence is based on the analysis of …

Should chatgpt be biased? challenges and risks of bias in large language models

E Ferrara - arxiv preprint arxiv:2304.03738, 2023‏ - arxiv.org
As the capabilities of generative language models continue to advance, the implications of
biases ingrained within these models have garnered increasing attention from researchers …

Ai alignment: A comprehensive survey

J Ji, T Qiu, B Chen, B Zhang, H Lou, K Wang… - arxiv preprint arxiv …, 2023‏ - arxiv.org
AI alignment aims to make AI systems behave in line with human intentions and values. As
AI systems grow more capable, so do risks from misalignment. To provide a comprehensive …

Explainable AI (XAI): Core ideas, techniques, and solutions

R Dwivedi, D Dave, H Naik, S Singhal, R Omer… - ACM Computing …, 2023‏ - dl.acm.org
As our dependence on intelligent machines continues to grow, so does the demand for more
transparent and interpretable models. In addition, the ability to explain the model generally …