Concepture: a regular language based framework for recognizing gestures with varying and repetitive patterns
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
We present Concepture, a framework based on regular language grammars for the authoring and recognition of sketched gestures with infinitely varying and repetitive patterns. Such gestures, while often seen in gesture based applications are currently hard-coded and not customizable. We endorse an example-based workflow, where users author gestures by sketching one or more example instances of the gesture. We de-construct these examples into perceptible stroke segments. Adjacent segment-pairs further capture local spatial relationships between segments and these segment-pairs form the alphabet of a regular language. We then initialize a grammar for our gesture by admitting strings that represent the user provided examples. Grammar refinement is user-friendly, in that we automatically generate new candidate gestures that are visually presented to the user for verification as instances of the gesture. We show Concepture to be effective in efficiently authoring a number of common, yet difficult to recognize gestures, and illustrate it using clip-art and image annotation applications.
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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 | 0.001 | 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