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Record W1988191034 · doi:10.1109/isit.2012.6283627

Space information flow: Multiple unicast

2012· article· en· W1988191034 on OpenAlex
Zongpeng Li, Chuan Wu

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicCooperative Communication and Network Coding
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsUnicastConjectureMulticastComputer scienceLinear network codingMathematicsTheoretical computer scienceTopology (electrical circuits)Coding (social sciences)Discrete mathematicsComputer networkCombinatoricsNetwork packet

Abstract

fetched live from OpenAlex

The multiple unicast network coding conjecture states that for multiple unicast in an undirected network, network coding is equivalent to routing. Simple and intuitive as it appears, the conjecture has remained open since its proposal in 2004 [1], [2], and is now a well-known unsolved problem in the field of network coding. In this work, we provide a proof to the conjecture in its space/geometric version. Space information flow is a new paradigm being proposed [3], [4]. It studies the transmission of information in a geometric space, where information flows are free to propagate along any trajectories, and may be encoded wherever they meet. The goal is to minimize a natural bandwidth-distance sum-product (network volume), while sustaining end-to-end unicast and multicast communication demands among terminals at known coordinates. The conjecture is true in networks only if it is true in space. Our main result is that network coding is indeed equivalent to routing in the space model. Besides its own merit, this partially verifies the original conjecture, and further leads to a geometric framework [5] for a hopeful proof to the conjecture.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.879
Threshold uncertainty score0.739

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.002
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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.

Opus teacher head0.038
GPT teacher head0.264
Teacher spread0.226 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it