<title>Distributed adaptation technique for mobile web browsing</title>
Bibliographic record
Abstract
The World Wide Web has become an essential tool as well as an entertainment medium in our daily life. However, efficient web browsing from anywhere at anytime, presents an opportunity as well as a challenge to the web document authors. The mobile users have a totally different requirement compared to the conventional wired users. The mobile networks have limited bandwidths, and the mobile terminals have limited resolutions. Hence a scheme is needed to adapt the web-data and multimedia contents such that they can be used on devices with limited resources such as bandwidth, resolution and memory space. In this paper we propose a novel mobile proxy server architecture suitable resource-limited multimedia terminals. Here, a distributed method is employed to adapt the multimedia data such that the adaptation is neither fully based on the proxy server nor fully based on the web server. Adaptation process is expected to be faster since the data adaptation loads are distributed between the proxy and the web server. Simulation results suggest that a significant performance improvement can be achieved with the proposed architecture.
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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".