Forward Error Protection for low-delay packet video
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 study different forward error correction (FEC) codes for packet video streaming over erasure channels with strict delay constraints. Our study includes traditional maximum distance separable (MDS) codes and streaming burst erasure codes with optimal delay performance. We develop a continuous-times model to calculate burst error correction capabilities of these codes with a delay constraint. Our analysis also incorporates Systematic Lossy Error Protection (SLEP) that achieves stronger error protection in exchange for a slight drop in video quality when error correction is needed. We provide simulation results for transmitting H.264/AVC encoded video over a bursty packet erasure channel and show that the combination of streaming erasure codes and SLEP greatly outperforms conventional MDS FEC for video streaming with a tight delay constraint.
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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 | 0.001 | 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