30 citations · 60 across the 10 of their papers we have counts for
10 papers
Eyettention II: A Dual-Sequence Architecture for Modeling Fixation Location, Within-Word Landing Position, and Fixation Duration in Reading
Shuwen Deng, Cui Ding, David R. Reich +2
The way our eyes move while reading provides valuable insights into both the reader's cognitive processes and the properties of the text. In particular, eye-tracking-while-reading…
Fixation Sequences as Time Series: A Topological Approach to Dyslexia Detection
Marius Huber, David R. Reich, Lena A. Jäger
Persistent homology, a method from topological data analysis, extracts robust, multi-scale features from data. It produces stable representations of time series by applying varying…
Eye-Tracking-while-Reading: A Living Survey of Datasets with Open Library Support
Deborah N. Jakobi, David R. Reich, Paul Prasse +3
Eye-tracking-while-reading corpora are a valuable resource for many different disciplines and use cases. Use cases range from studying the cognitive processes underlying reading to…
Modeling Bottom-up Information Quality during Language Processing
Cui Ding, Yanning Yin, Lena A. Jäger +1
Contemporary theories model language processing as integrating both top-down expectations and bottom-up inputs. One major prediction of such models is that the quality of the botto…
Reporting Eye-Tracking Data Quality: Towards a New Standard
Deborah N. Jakobi, Daniel G. Krakowczyk, Lena A. Jäger
Eye-tracking datasets are often shared in the format used by their creators for their original analyses, usually resulting in the exclusion of data considered irrelevant to the pri…
Pre-Trained Language Models Augmented with Synthetic Scanpaths for Natural Language Understanding
Shuwen Deng, Paul Prasse, David R. Reich +2
Human gaze data offer cognitive information that reflects natural language comprehension. Indeed, augmenting language models with human scanpaths has proven beneficial for a range…
Bridging the Gap: Gaze Events as Interpretable Concepts to Explain Deep Neural Sequence Models
Daniel G. Krakowczyk, Paul Prasse, David R. Reich +3
Recent work in XAI for eye tracking data has evaluated the suitability of feature attribution methods to explain the output of deep neural sequence models for the task of oculomotr…
pymovements: A Python Package for Eye Movement Data Processing
Daniel G. Krakowczyk, David R. Reich, Jakob Chwastek +6
We introduce pymovements: a Python package for analyzing eye-tracking data that follows best practices in software development, including rigorous testing and adherence to coding s…
Detection of ADHD based on Eye Movements during Natural Viewing
Shuwen Deng, Paul Prasse, David R. Reich +7
Attention-deficit/hyperactivity disorder (ADHD) is a neurodevelopmental disorder that is highly prevalent and requires clinical specialists to diagnose. It is known that an individ…
Reading Task Classification Using EEG and Eye-Tracking Data
Nora Hollenstein, Marius Tröndle, Martyna Plomecka +4
The Zurich Cognitive Language Processing Corpus (ZuCo) provides eye-tracking and EEG signals from two reading paradigms, normal reading and task-specific reading. We analyze whethe…