Bibliographic record
Abstract
We present HaptoBend, a novel shape-changing input device providing passive haptic feedback (PHF) for a wide spectrum of objects in virtual reality (VR). Past research in VR shows that PHF increases presence and improves user task performance. However, providing PHF for multiple objects usually requires complex, immobile systems, or multiple props. HaptoBend addresses this problem by allowing users to bend the device into 2D plane-like shapes and multi-surface 3D shapes. We believe HaptoBend's physical approximations of virtual objects can provide realistic haptic feedback through research demonstrating the dominance of human vision over other senses in VR. To test the effectiveness of HaptoBend in matching 2D planar and 3D multi-surface shapes, we conducted an experiment modeled after gesture elicitation studies with 20 participants. High goodness and ease scores show shape-changing passive haptic devices, like HaptoBend, are an effective approach to generalized haptics. Further analysis supports the use of physical approximations for realistic haptic feedback.
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.
How this classification was reachedexpand
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) | 0.001 | 0.001 |
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 itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".