Improving LZ77 bit recycling using all matches
Why this work is in the frame
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Bibliographic record
Abstract
There exist lossless compression techniques, such as LZ77, that have the particularity that some original file may be compressed in more than one way, e.g. by choosing other matches than the closest longest ones only. The existence of multiple encodings per original file causes redundancy, i.e. it tends to make compressed files longer than necessary, on average. Recently, a technique called bit recycling was introduced to help reduce the redundancy caused by the multiplicity of encodings. It has been used to improve LZ77 compression. It exploits the fact that there often exists more than one longest match and it is called longest-match bit recycling. This work presents a more general, and more powerful, bit recycling technique that exploits shorter matches also. We call the technique all-match bit recycling. Our experiments demonstrate that at least 1 bit out of 11 results from the multiplicity of encodings, in LZ77 compression.
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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 | 0.001 |
| 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