Improved MDLNS Number System Addition and Subtraction by Use of the Novel Co- Transformation
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
Multi-Dimensional Logarithmic Number System (MDLNS) is a generalized version of the Logarithmic Number System (LNS) which has multiple dimensions or bases. These generalizations can increase accuracy and hardware efficiency. However, addition and subtraction operations are the major obstruction of all logarithmic number systems circuits and so far a fair amount of research has been done to find practical techniques in LNS to implement these operations efficiently without the need for large tables. In order to achieve this goal, several methods such as interpolation, multipartite tables, and co-transformation have been introduced to decrease the cost and complexity. One of the most recent works is Novel Co-transformation. This thesis investigates the application of the Novel Co-Transformation on MDLNS. The goal is to reduce the table sizes over previously published method which utilizes a different address decoder on its tables which requires greater overhead. The results show that the table sizes are reduced significantly when a minimal error is allowed. Other common LNS techniques for table reductions may be applied to obtain better results.
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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 | 0.000 | 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