Improving Compression via Substring Enumeration by Explicit Phase Awareness
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.
Bibliographic record
Abstract
Compression by Substring Enumeration (CSE) is a recent and promising lossless compression scheme. The first experiments on CSE showed that it yields compression ratios that favorably compare to other lossless compression techniques. However, the experiments also showed that it tends to incur a performance loss on non-textual, byte-oriented sources and it was conjectured that CSE's phase unawareness was responsible for this loss of performance. Subsequent work confirmed the conjecture by obtaining improved compression ratios when synchronization codes get inserted in the data source, indirectly solving the phase-unawareness problem. This indirect solution does not give an absolute measure of the loss incurred by the phase unawareness problem. This paper presents a modified CSE algorithm that is made explicitly phase aware. It compares the synchronization-code approach to the explicitly phase-aware approach and shows that, in the end, the approach based on synchronization codes is almost as good as the phase-aware approach.
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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 | 0.001 |
| 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 it