String searching with mismatches using AVX2 and AVX-512 instructions
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
We present new algorithms for the k mismatches version of approximate string matching. Our algorithms utilize the SIMD (Single Instruction Multiple Data) instruction set extensions, particularly AVX2 and AVX-512 instructions. Our approach is an extension of an earlier algorithm for exact string matching with SSE2 and AVX2. In addition, we modify this exact string matching algorithm to work with AVX-512. We demonstrate the competitiveness of our solutions by practical experiments. Our algorithms outperform earlier algorithms for both exact and approximate string matching on various benchmark data sets. • New algorithms for the k mismatches version of approximate string matching. • We modify the exact string-matching algorithm to work with AVX-512. • Demonstrate the competitiveness of our solutions by practical experiments.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.006 |
| 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