HawKEY: Efficient and Versatile Text Entry for Virtual Reality
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Text entry is still a challenging task in modern Virtual Reality (VR) systems. The lack of efficient text entry methods limits the applications that can be used productively in VR. Previous work has addressed this issue through virtual keyboards or showing the physical keyboard in VR. While physical keyboards afford faster text entry, they usually require a seated user and an instrumented environment. We introduce a new keyboard, worn on a hawker’s tray in front of the user, which affords a compact, simple, flexible, and efficient text entry solution for VR, without restricting physical movement. In our new video condition, we also show the keyboard only when the user is looking down at it. To evaluate our novel solution and to identify good keyboard visualizations, we ran a user study where we asked participants to enter both lowercase sentences as well as complex text while standing. The results show that text entry rates are affected negatively by simplistic keyboard visualization conditions and that our solution affords desktop text entry rates, even when standing.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it