<title>Content adaptation architecture with efficient usage of cached data in a multimedia proxy server</title>
Bibliographic record
Abstract
The use of multimedia data is growing at a rapid rate, and bringing multimedia services to terminals with limited capabilities is a major challenge. Efficient schemes are hence required for adapating the multimedia content for delivery to devices with limited resources. In the conventional server and proxy-based architectures, the adaptation is performed either at the server or at the proxy resulting in the loading of the server and the proxy. In this paper we propose a novel distributed adaptation architecture suitable for resource-limited multimedia terminals as well as wired connections with high bandwidths. Here, the data can be adapted at the proxy or at the server, resulting in a faster adaptation process. In addition, we propose an efficient cache replacement policy at the proxy. The proposed architecture is very flexible for both mobile and wired networks. The experimental results show that the proposed architecture improves the performance of the proxy and the server, and reduces network congestion and latency.
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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 | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".