An adaptation mechanism for robust OTT video transmission
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
“Over the top” (OTT) has become an increasingly popular form of delivery for voice and video communications. Ubiquitous OTT communications, pioneered by Skype, have, with the recent release of WebRTC, become a commodity readily available for various applications, without a need for extra installations. Still, in spite of such progress, media communications remain challenging as user expectations are keeping ahead of technology progress and portable devices are becoming the norm. In practical terms, this means that media flows must constantly adapt to varying network conditions to try to -reliably!- offer the best experience to the users. We present in this paper a sender-side adaptation algorithm for video flows which trades off redundancy and throughput to maximize quality while minimizing the likelihood of loss, thus preserving service continuity. By exploiting standard FEC mechanisms at different levels of redundancy while controlling the quality of media delivered, we create a discrete parameter space which the algorithm exploits based on quality feedback. We study the performance of this algorithm in a number of reference test cases and discuss how it improves on earlier and related proposals.
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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 | 0.000 | 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