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 # Eyettention: An Attention-based Dual-Sequence Model for Predicting Human Scanpaths during Reading
 
 In this paper, we develop Eyettention, the first dual-sequence model that simultaneously processes the sequence of words and the chronological sequence of fixations. The alignment of the two sequences is achieved by a cross-sequence attention mechanism. We show that Eyettention outperforms state-of-the-art models in predicting scanpaths. We provide an extensive within- and across-data set evaluation on different languages. An ablation study and qualitative analysis support an in-depth understanding of the model's behavior.
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 ## License
 
-The original code is provided under the [MIT License](LICENSE.txt), copyright © 2023 AEye. Include the copyright and permission notice when redistributing copies or substantial portions of the software. See the license file for the full terms and warranty disclaimer. Datasets and dependencies retain their own licenses.
+The original code is provided under the [MIT License](LICENSE.txt), copyright © 2023 AEye. Include the copyright and permission notice when redistributing copies or substantial portions of the software. See the license file for the full terms and warranty disclaimer. Datasets and dependencies retain their own licenses.