Activity counts measure attention, not model quality. Missing counts are unknown. Publication status follows the linked source; a listed venue alone does not confirm peer review.
- Signals
- IMU
- License
none declared (no LICENSE file in repo at the recorded commit; all rights reserved by default)
- Type
- Task model
- Modalities
- IMU
- Form factor
- Not reported
- Parameters
- Not reported
- Architecture
- Not reported
- Venue
- Not reported
- Year
- Not reported
- arXiv
- Not reported
- DOI
- Not reported
- Weights
- Not released
- Licence
- none declared (no LICENSE file in repo at the recorded commit; all rights reserved by default)
- Caveats
- Not reported
- Datasets
- Not reported
- Added
- Oct 19, 2026
- Updated
- Oct 19, 2026
Original description
Official repository for TRACE-TS: Attribution-Grounded and Traceable Sensor-Language Reasoning for Human Activity Understanding.
The paper provides detailed implementation details, including model architecture, training objectives, attribution-grounded distillation, and experimental protocols across seven HAR benchmarks.
Verbatim fromGitHub· Description from the repository README
How it works
- Inputs
- IMU
- Approach
- code release · no weights
Datasets
Papers· 1
Cite
APA
TRACE-TS. (n.d.).
BibTeX
@misc{tracetstracets,
title = {{TRACE-TS}}
}Built from the hub record. Check it against the publisher before submitting.
History
Added to the ChatPPG research hub