ZORA Publication List

Publications

• Jakobi, D. N., Reich, D. R., Prasse, P., Hofmann, J. M., Bolliger, L. S., & Jäger, L. A. (2026). Eye-tracking-while-reading: A living survey of datasets with open library support Behavior Research Methods, 58, 263. https://doi.org/10.3758/s13428-026-03126-6
• Deng, S., Ding, C., Reich, D. R., Prasse, P., & Jäger, L. A. (2026). Eyettention II: A dual-sequence architecture for modeling fixation location, within-word landing position, and fixation duration in reading Behavior Research Methods, 58, 257. https://doi.org/10.3758/s13428-026-03118-6
• Huber, M., Reich, D. R., & Jäger, L. A. (2026). Fixation Sequences as Time Series: A Topological Approach to Dyslexia Detection (A. Chetouani & A. Vilanueva, Eds.; p. 12). ACM Digital library. https://doi.org/10.1145/3797246.3803045
• Haller, P., Ding, C., Stegenwallner-Schütz, M., Reich, D. R., Koncic, I., Makowski, S., & Jäger, L. A. (2025). Replicate Me if You Can: Assessing Measurement Reliability of Individual Differences in Reading Across Measurement Occasions and Methods Cognitive Science, 50, e70121. https://doi.org/10.1111/cogs.70121
• Shubi, O., Reich, D. R., Grutke Klein, K., Angel, Y., Prasse, P., Jäger, L., & Berzak, Y. (2025). EyeBench: Predictive Modeling from Eye Movements in Reading (No. 39). online.
• Siegelman, N., Schroeder, S., Bao, Y. B., Acartürk, C., Agrawal, N., Bolliger, L. S., Brasser, J., Campos-Rojas, C., Drieghe, D., Filipović Đurđević, D., Goldina, S., Ibáñez Orellana, R., Jäger, L., Jóhannesson, Ó. I., Khare, A., Kharlamov, N., Knudsen, H. B. S., Kristjánsson, Á., Lee, C. E., … et al. (2025). Wave 2 of the Multilingual Eye-Movement Corpus (MECO): New text reading data across languages Scientific Data, 12, 1183. https://doi.org/10.1038/s41597-025-05453-3
• Bolliger, L. S., Haller, P., Cretton, I. C. R., Reich, D. R., Kew, T., & Jäger, L. (2025). EMTeC: A Corpus of Eye Movements on Machine-Generated Texts Behavior Research Methods, 57, 189. https://doi.org/10.3758/s13428-025-02677-4
• Jakobi, D. N., Reich, D. R., Prasse, P., & Jäger, L. A. (2025). Neural Additive Models Uncover Predictive Gaze Features in Reading Proceedings of the Symposium on Eye Tracking Research and Applications, 1–10. https://doi.org/10.1145/3715669.3723117
• Bondar, A., Reich, D. R., & Jäger, L. A. (2025). CoLAGaze: A Corpus of Eye Movements for Linguistic Acceptability (Y. Sugano, M. Khamis, A. Chetouani, & et al, Eds.; No. 9; p. 9). ACM Digital library. https://doi.org/10.1145/3715669.3723120
• Prasse, P., Reich, D. R., Chwastek, J., Makowski, S., Jäger, L. A., & Scheffer, T. (2025). Detection of Alcohol Inebriation from Eye Movements using Remote and Wearable Eye Trackers Proceedings of the Symposium on Eye Tracking Research and Applications, 1–10. https://doi.org/10.1145/3715669.3723109
• Jakobi, D. N., Stegenwallner-Schütz, M., Hollenstein, N., Ding, C., Kasperė, R., Matić Škorić, A., Pavlinušić Vilus, E., Frank, S., Müller, M.-L., Jensen De López, K. M., Kharlamov, N., Knudsen, H. B. S., Berzak, Y., Lion, E., Sekerina, I., Acarturk, C., ANSARI, M. F., Harezlak, K., Kasprowski, P., … Jäger, L. (2025). MultiplEYE: Creating a Multilingual Eye-Tracking-While-Reading Corpus (Y. Sugano, M. Khamis, A. Chetouani, L. Sidenmark, & A. Bruno, Eds.; p. 111). ACM Digital library. https://doi.org/10.1145/3715669.3726843
• Krakowczyk, D. G., Reich, D. R., Säuberli, A., Škrjanec, I., Cretton, I. C. R., Jakobi, D. N., Nisioi, S., Prasse, P., & Jäger, L. A. (2025). The More the Merrier: Boost Your Dataset Visibility and Discover Eye-Tracking Datasets with pymovements (Y. Sugano, M. Khamis, A. Chetouani, L. Sidenmark, & A. Bruno, Eds.; p. 63). ACM Digital library. https://doi.org/10.1145/3715669.3726810
• Reich, D. R., Ding, C., Bolliger, L. S., Haller, P., Prasse, P., & Jäger, L. A. (2025). Proxy-Based Pre-Training for Eye-Tracking Applications (Y. Sugano, M. Khamis, A. Chetouani, L. Sidenmark, & A. Bruno, Eds.; p. 26). ACM Digital library. https://doi.org/10.1145/3715669.3723113
• Reich, D. R., Prasse, P., & Jäger, L. A. (2025). Evaluating Gaze Event Detection Algorithms: Impacts on Machine Learning-based Classification and Psycholinguistic Statistical Modeling Proceedings of the ACM on Human-Computer Interaction, 9, ETRA10. https://doi.org/10.1145/3725835
• Bolliger, L. S., Reich, D. R., & Jäger, L. A. (2025). ScanDL 2.0: A Generative Model of Eye Movements in Reading Synthesizing Scanpaths and Fixation Durations Proceedings of the ACM on Human-Computer Interaction, 9, ETRA05. https://doi.org/10.1145/3725830
• Jakobi, D. N., Kern, T., Reich, D. R., Haller, P., & Jäger, L. (2025). PoTeC: a German Naturalistic Eye-Tracking-While-Reading Corpus Behavior Research Methods, 57, 211. https://doi.org/10.3758/s13428-024-02536-8
• Bondar, A., Reich, D. R., & Jäger, L. (2025). AlEYEgnment: Leveraging Eye-Tracking-While-Reading to Align Language Models with Human Preferences (C. Acarturk, J. Nasir, B. Can, & Ç. Çöltekin, Eds.; No. 1; pp. 58–70). Association for Computational Linguistics. https://aclanthology.org/2025.gaze4nlp-1.8/
• Kuperman, V., Schroeder, S., Acartürk, C., Agrawal, N., Alexandre, D. M., Bolliger, L. S., Brasser, J., Campos-Rojas, C., Drieghe, D., et al, Reich, D. R., & Jäger, L. (2025). New data on text reading in English as a second language: The Wave 2 expansion of the Multilingual Eye-Movement Corpus (MECO) Studies in Second Language Acquisition, 47, 677–695. https://doi.org/10.1017/S0272263125000105
• Wu, G., Bolliger, L. S., Reich, D. R., & Jäger, L. A. (2024). An Eye Opener Regarding Task-Based Text Gradient Saliency (T. Kuribayashi, G. Rambelli, E. Takmaz, & et al, Eds.; pp. 255–263). Association for Computational Linguistics. https://doi.org/10.18653/v1/2024.cmcl-1.22
• Kiegeland, S., Reich, D., Cotterell, R., Jäger, L., & Wilcox, E. (2024). The Pupil Becomes the Master: Eye-Tracking Feedback for Tuning LLMs online. https://openreview.net/pdf?id=8oLUcBgKua
• Alakmeh, T., Reich, D., Jäger, L., & Fritz, T. (2024). Predicting code comprehension: a novel approach to align human gaze with code using deep neural networks (Vol. 1, No. FSE, Article 88). 1982–2004. https://doi.org/10.1145/3660795
• Reich, D. R., Deng, S., Björnsdóttir, M., Jäger, L. A., & Hollenstein, N. (2024). Reading Does Not Equal Reading: Comparing, Simulating and Exploiting Reading Behavior Across Populations 13586–13594. https://aclanthology.org/2024.lrec-main.1187/
• Prasse, P., Reich, D. R., Makowski, S., Scheffer, T., & Jäger, L. A. (2024). Improving cognitive-state analysis from eye gaze with synthetic eye-movement data Computers & Graphics, 119, 103901. https://doi.org/10.1016/j.cag.2024.103901
• Deng, S., Prasse, P., Reich, D. R., Scheffer, T., & Jäger, L. A. (2024). Fine-Tuning Pre-Trained Language Models with Gaze Supervision 217–224. https://doi.org/10.18653/v1/2024.acl-short.21
• Bolliger, L. S., Reich, D. R., Haller, P., Jakobi, D. N., Prasse, P., & Jäger, L. A. (2023). ScanDL: A Diffusion Model for Generating Synthetic Scanpaths on Texts (H. Bouamor, J. Pino, & K. Bali, Eds.; pp. 15513–15538). Association for Computational Linguistics. https://doi.org/10.18653/v1/2023.emnlp-main.960
• Prasse, P., Reich, D. R., Makowski, S., Ahn, S., Scheffer, T., & Jäger, L. A. (2023). SP-EyeGAN: Generating Synthetic Eye Movement Data with Generative Adversarial Networks Proceedings of the Symposium on Eye Tracking Research and Applications, 18. https://doi.org/10.1145/3588015.3588410
• Krakowczyk, D. G., Prasse, P., Reich, D. R., Lapuschkin, S., Scheffer, T., & Jäger, L. A. (2023). Bridging the Gap: Gaze Events as Interpretable Concepts to Explain Deep Neural Sequence Models (E. Kasneci, F. Shic, & M. Khamis, Eds.; p. 3). ACM Digital library. https://doi.org/10.1145/3588015.3588412
• Deng, S., Reich, D. R., Prasse, P., Haller, P., Scheffer, T., & Jäger, L. A. (2023). Eyettention: An Attention-based Dual-Sequence Model for Predicting Human Scanpaths during Reading Proceedings of the ACM on Human-Computer Interaction, 7, 162. https://doi.org/10.1145/3591131
• Deng, S., Prasse, P., Reich, D. R., Scheffer, T., & Jäger, L. A. (2023). Pre-Trained Language Models Augmented with Synthetic Scanpaths for Natural Language Understanding (H. Bouamor, J. Pino, & K. Bali, Eds.; pp. 6500–6507). Association for Computational Linguistics. https://doi.org/10.18653/v1/2023.emnlp-main.400
• Krakowczyk, D. G., Reich, D. R., Chwastek, J., Jakobi, D. N., Prasse, P., Süss, A., Turuta, O., Kasprowski, P., & Jäger, L. A. (2023). pymovements: A Python Package for Eye Movement Data Processing (E. Kasneci, F. Shic, & M. Khamis, Eds.; p. 53). ACM Digital library. https://doi.org/10.1145/3588015.3590134
• Krakowczyk, D., Reich, D. R., Prasse, P., Lapuschkin, S., Scheffer, T., & Jäger, L. A. (2022). Selection of XAI methods matters: Evaluation of feature attribution methods for oculomotoric biometric identification (210:66-97). 1–31. https://proceedings.mlr.press/v210/krakowczyk23a
• Deng, S., Prasse, P., Reich, D. R., Dziemian, S., Stegenwallner-Schütz, M., Krakowczyk, D. G., Makowski, S., Langer, N., Scheffer, T., & Jäger, L. A. (2022). Detection of ADHD based on eye movements during natural viewing 403–418. https://doi.org/10.1007/978-3-031-26422-1_25
• Reich, D. R., Prasse, P., Tschirner, C., Haller, P., Goldhammer, F., & Jäger, L. A. (2022). Inferring Native and Non-Native Human Reading Comprehension and Subjective Text Difficulty from Scanpaths in Reading 23. https://doi.org/10.1145/3517031.3529639
• Prasse, P., Reich, D. R., Makowski, S., Jäger, L. A., & Scheffer, T. (2022). Fairness in Oculomotoric Biometric Identification (F. Shic, E. Kasneci, M. Khamis, & et al, Eds.; p. 22). ACM Digital library. https://doi.org/10.1145/3517031.3529633
• Makowski, S., Prasse, P., Reich, D. R., Krakowczyk, D., Jäger, L. A., & Scheffer, T. (2021). DeepEyedentificationLive: Oculomotoric Biometric Identification and Presentation-Attack Detection using Deep Neural Networks IEEE Transactions on Biometrics, Behavior, and Identity Science, 3, 506–518. https://doi.org/10.1109/tbiom.2021.3116875