This study integrates Bundesen’s Theory of Visual Attention (TVA) with task-evoked pupillary responses (TEPR) to examine how typog- raphy affects letter recognition. Twenty-one participants completed a whole-report task with Danish letters in three fonts (Cambria, Garamond, Roboto)× two styles (Regular, Italic) across eight expo- sure durations (10–200 ms). Bayesian posterior analysis revealed that italic processing-speed penalties scale with the degree of structural redesign: Garamond’s script-derived italic imposed the largest cost (Δ= 27.0 elem/s, (Δ > 0)= 1.00), Cambria’s glyph substitutions a moderate cost (Δ= 16.8, = 1.00), and Roboto’s oblique the smallest (Δ= 4.5, = 0.82, CI spanning zero). Pupillary metrics showed no significant font effects; only exposure duration drove dilation, though dPPD revealed a significant Font× Style interaction. This dissociation font-sensitive TVA parameters but font-insensitive pupillary am- plitude suggests typography modulates encoding efficiency rather than cognitive effort, although pupillometric

While Generative AI models like Large Language Models (LLMs) are capable of generating extensive text, their efficacy in producing readable content for human participants in experimental settings remains to be evaluated. Further, eye-tracking technology is increas- ingly utilized to study cognition and behavior, yet its application to readers’ cognitive processes when exposed to AI-generated versus human-authored texts remains unexplored. This study investigates how text generated by LLMs influences reading by analyzing gaze patterns. The study collects gaze data from 13 participants as they read AI- generated and human-authored passages. A comparative analysis is conducted within subjects to assess gaze patterns between authors and between text types based on the robust two-means clustering (I2MC) algorithm to identify fixations. In addition, pupil dilation and reading speed were examined. Our findings reveal significant differences in fixation character- istics not only between authors but also between AI-generated and human-authored texts.

While adaptive reading interfaces are capable of providing flexible typographical adjustments in real-time, readers are challenged to keep track of the context. This paper aims to contribute by introducing context preservation, which enables readers to resume reading faster after applying typographical adjustments, using eye-tracking. Typography adjustments are applied through so-called interventions, and the reading application currently has four intervention designs: Popup, Undo, Notification, and Gradual. To explore how much text is required to resume reading quickly, context-preservation functionality was applied and evaluated on 22 participants through within-subjects experiment design. Our findings reveal significant differences in reading-resume time (RRT) between interventions. Furthermore, context-preservation in a gradual intervention mode is the fastest and most liked intervention design by the participants.

Within the last 20 years, gaze interaction has become a successful communication solution for numerous people with motor challenges. In this paper, we present two new cases of gaze interactive assistive technology: i) gaze control of an exoskeleton for stroke rehabilitation, and ii) gaze interactive reading support for people with low vision. By applying a Universal Design approach [Mace 1998] both cases are assessed through an ability analysis to identify issues with gaze interaction specific to our applications that need to be further addressed. Finally, we suggest how solutions in our applications may be mainstreamed for a broader user group.