Abstract
This paper investigates the technical potential of developing explainable transformer-based large language models (LLMs) that meet users' needs and comply with regulations such as the EU AI Act. We implement and evaluate a proof-of-concept explainable LLM-based system. Furthermore, we demonstrate its potential for regulatory compliance and identify technical challenges to be tackled.
Cite
CITATION STYLE
Górski, Ł., & Ramakrishna, S. (2023). Challenges in Adapting LLMs for Transparency: Complying with Art. 14 EU AI Act. In Frontiers in Artificial Intelligence and Applications (Vol. 379, pp. 275–280). IOS Press BV. https://doi.org/10.3233/FAIA230974
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