Demo Data from EDBT 2026 / reviewers in the wild / expert
Benjamin Yang
dblp:220/2857
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2026
0009-0006-0284-169XORCID · reported
Domains — the database's venue-derived domains; a paper can count in several
Human-computer interaction and ubiquitous computing · 1 · 1 since 2021
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Human-computer interaction and pervasive computing
1 paper |
Interaction techniques and input · 100% | |
| Computer graphics and multimedia
1 paper |
Virtual and augmented reality · 100% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Interaction techniques and input › text entry
gesture-based text entry |
1.0 | 1 | 2026 | SwEYEpinch and Beyond: Exploring Intuitive, Efficient Text Entry for Extended Reality via Eye and Hand Tracking · CHI 2026 |
Interaction techniques and input
text entry |
1.0 | 1 | 2026 | SwEYEpinch and Beyond: Exploring Intuitive, Efficient Text Entry for Extended Reality via Eye and Hand Tracking · CHI 2026 |
Virtual and augmented reality › immersive interaction
extended reality interaction |
0.3 | 1 | 2026 | SwEYEpinch and Beyond: Exploring Intuitive, Efficient Text Entry for Extended Reality via Eye and Hand Tracking · CHI 2026 |
Methods — techniques the papers use, named apart from their topics
user study · 2.0dynamic time warping · 2.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2026 | SwEYEpinch and Beyond: Exploring Intuitive, Efficient Text Entry for Extended Reality via Eye and Hand TrackingabstractDespite steady progress, text entry in Extended Reality (XR) often remains slower and more effortful than typing on a physical keyboard or touchscreen. We explore a simple idea: use gaze to swipe through a virtual keyboard for the fast, low-effort where and a manual pinch held throughout the swipe for the when, extending and validating it through a series of user studies. We first show that a basic version including a low-latency decoder with spatiotemporal Dynamic Time Warping and fixation filtering outperforms selecting individual keys sequentially, either by finger tapping each or gazing at each while pinching. We then add mid-swipe prediction and in-gesture cancellation, improving words per minute (WPM) without hurting accuracy. We show that this approach is faster and more preferred than previous gaze-swipe approaches, finger tapping with prediction, or hand swiping with the same additions. Furthermore, a seven-day, 30-session study demonstrates sustained learning, with peak performance reaching 64.7 WPM. Ziheng 'Leo' Li, Xichen He, Mengyuan Wu, Zeyi Tong, Haowen Wei, Benjamin Yang, Steven K. Feiner, Paul Sajda |
CHI | 6 |