@article{Schwenke_Atzmueller_2021, title={Show Me What You’re Looking For: Visualizing Abstracted Transformer Attention for Enhancing Their Local Interpretability on Time Series Data}, volume={34}, url={https://journals.flvc.org/FLAIRS/article/view/128399}, DOI={10.32473/flairs.v34i1.128399}, abstractNote={<pre>While Transformers have shown their advantages considering<br>their learning performance, their lack of explainability<br>and interpretability is still a major problem.<br>This specifically relates to the processing of time series,<br>as a specific form of complex data. In this paper,<br>we propose an approach for visualizing abstracted information<br>in order to enable computational sensemaking<br>and local interpretability on the respective Transformer<br>model. Our results demonstrate the efficacy of<br>the proposed abstraction method and visualization, utilizing<br>both synthetic and real world data for evaluation.</pre>}, journal={The International FLAIRS Conference Proceedings}, author={Schwenke, Leonid and Atzmueller, Martin}, year={2021}, month={Apr.} }