2 papers
cs.CL2026
LLMs Explain't: A Post-Mortem on Semantic Interpretability in Transformer Models
Alhassan Abdelhalim, Janick Edinger, Sören Laue +1
Large Language Models (LLMs) are becoming increasingly popular in pervasive computing due to their versatility and strong performance. However, despite their ubiquitous use, the ex…
cs.CL2025
Prediction is not Explanation: Revisiting the Explanatory Capacity of Mapping Embeddings
Hanna Herasimchyk, Alhassan Abdelhalim, Sören Laue +1
Understanding what knowledge is implicitly encoded in deep learning models is essential for improving the interpretability of AI systems. This paper examines common methods to expl…