Efficient communication in unknown networks
Why this work is in the frame
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Bibliographic record
Abstract
Abstract We consider the problem of disseminating messages in networks. We are interested in information dissemination algorithms in which machines operate independently without any knowledge of the network topology or size. Three communication tasks of increasing difficulty are studied. In blind broadcasting (BB), the goal is to communicate the source message to all nodes. In acknowledged blind broadcasting (ABB), the goal is to achieve BB and inform the source about it. Finally, in full synchronization (FS), all nodes must simultaneously enter the state terminated after receiving the source message. The algorithms should be efficient both in terms of the time required and the communication overhead they put on the network. We limit the latter by allowing every node to send a message to at most one neighbor in each round. We show that BB is achieved in time at most 2 n in any n ‐node network and show networks in which time 2 n − o ( n ) is needed. For ABB, we show algorithms working in time (2 + ϵ) n , for any fixed positive constant ϵ and sufficiently large n . Thus, for both BB and ABB, our algorithms are close to optimal. Finally, we show a simple algorithm for FS working in time 3 n and a more complicated algorithm which works in time 2.9 n . The optimal time of full synchronization remains an open problem. © 2001 John Wiley & Sons, Inc.
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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