New Heuristic for Message Broadcasting in Networks
Why this work is in the frame
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Bibliographic record
Abstract
In this paper, we present a new heuristic that generates broadcast schemes in arbitrary networks. The heuristic gives optimal broadcast time for HyperCube, and best results for Cube-Connected Cycles and large Shuffle-Exchange graphs. Extensive simulations show that our new heuristic outperforms the best known broadcast algorithms for two different network models representing Internet generated using BRITE (Boston university Representative Internet Topology gEnerator). It also has a low time complexity, O(\E\log\V\), which is lower compared to the complexities of most of the other good algorithms. The last advantage of the heuristic is that approximately one half of the nodes are informed via a shortest path from the originator, while the rest of the vertices receive the message via a path at most three hops longer.
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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