Datasets:

toksuite
/

tokenizer_robustness_completion_stem

@@ -2668,48 +2668,30 @@ Each perturbation preserves the **underlying semantic intent** of the canonical
 ### 1. Canonical
 Clean, standard technical English with conventional notation, spacing, and formatting. This serves as the reference condition for evaluating robustness.
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 ### 2. Character Deletion
 Removes one or more characters from technical terms, symbols, or variables (e.g., `markup → markp`). These deletions are subtle but often catastrophic for subword tokenization, especially in STEM terminology.
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 ### 3. Colloquial
 Rewrites the question using more informal or descriptive language while preserving technical meaning. This tests robustness to register changes without altering core content.
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 ### 4. Compounds
 Alters compound technical terms by merging or restructuring components (e.g., removing separators or introducing fused forms), changing token boundaries and segmentation behavior.
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 ### 5. Diacriticized Styling
 Introduces decorative or combining diacritics applied to characters in technical text. These perturbations preserve visual similarity but change Unicode code points and normalization behavior.
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 ### 6. Double-Struck Characters
 Replaces standard Latin characters with mathematical double-struck Unicode forms (e.g., `R → ℝ`, `Z → ℤ`), commonly used in mathematical notation.
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 ### 7. Enclosed Characters
 Substitutes alphanumeric characters with enclosed Unicode variants (e.g., `A → Ⓐ`, `1 → ①`), which are visually similar but tokenized very differently.
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 ### 8. Equivalent Expressions
 Rewrites the same STEM concept using an alternative but semantically equivalent formulation, such as paraphrasing definitions or reordering explanatory clauses.
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 ### 9. Fullwidth Characters
 Uses fullwidth Unicode forms (e.g., `A → Ａ`, `1 → １`) instead of standard ASCII characters, altering byte-level and subword tokenization.
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 ### 10. LaTeX
 Represents mathematical expressions or symbols using LaTeX-style notation (e.g., `$x^2$`, `$N_2$`, `\frac{a}{b}`), reflecting common technical writing practices.

 ### 1. Canonical
 Clean, standard technical English with conventional notation, spacing, and formatting. This serves as the reference condition for evaluating robustness.
 ### 2. Character Deletion
 Removes one or more characters from technical terms, symbols, or variables (e.g., `markup → markp`). These deletions are subtle but often catastrophic for subword tokenization, especially in STEM terminology.
 ### 3. Colloquial
 Rewrites the question using more informal or descriptive language while preserving technical meaning. This tests robustness to register changes without altering core content.
 ### 4. Compounds
 Alters compound technical terms by merging or restructuring components (e.g., removing separators or introducing fused forms), changing token boundaries and segmentation behavior.
 ### 5. Diacriticized Styling
 Introduces decorative or combining diacritics applied to characters in technical text. These perturbations preserve visual similarity but change Unicode code points and normalization behavior.
 ### 6. Double-Struck Characters
 Replaces standard Latin characters with mathematical double-struck Unicode forms (e.g., `R → ℝ`, `Z → ℤ`), commonly used in mathematical notation.
 ### 7. Enclosed Characters
 Substitutes alphanumeric characters with enclosed Unicode variants (e.g., `A → Ⓐ`, `1 → ①`), which are visually similar but tokenized very differently.
 ### 8. Equivalent Expressions
 Rewrites the same STEM concept using an alternative but semantically equivalent formulation, such as paraphrasing definitions or reordering explanatory clauses.
 ### 9. Fullwidth Characters
 Uses fullwidth Unicode forms (e.g., `A → Ａ`, `1 → １`) instead of standard ASCII characters, altering byte-level and subword tokenization.
 ### 10. LaTeX
 Represents mathematical expressions or symbols using LaTeX-style notation (e.g., `$x^2$`, `$N_2$`, `\frac{a}{b}`), reflecting common technical writing practices.