---
license: cc
multilinguality: multilingual
task_categories:
- multiple-choice
pretty_name: Tokenization Robustness
tags:
- multilingual
- tokenization
dataset_info:
- config_name: code_technical_content_buggy_code
  features:
  - name: question
    dtype: string
  - name: choices
    sequence: string
  - name: answer
    dtype: int64
  - name: answer_label
    dtype: string
  - name: split
    dtype: string
  - name: subcategories
    dtype: string
  - name: lang
    dtype: string
  - name: second_lang
    dtype: string
  - name: coding_lang
    dtype: string
  - name: notes
    dtype: string
  - name: id
    dtype: string
  - name: set_id
    dtype: float64
  - name: variation_id
    dtype: string
  splits:
  - name: test
    num_bytes: 7633
    num_examples: 21
  download_size: 8410
  dataset_size: 7633
- config_name: code_technical_content_cannonical
  features:
  - name: question
    dtype: string
  - name: choices
    sequence: string
  - name: answer
    dtype: int64
  - name: answer_label
    dtype: string
  - name: split
    dtype: string
  - name: subcategories
    dtype: string
  - name: lang
    dtype: string
  - name: second_lang
    dtype: string
  - name: coding_lang
    dtype: string
  - name: notes
    dtype: string
  - name: id
    dtype: string
  - name: set_id
    dtype: float64
  - name: variation_id
    dtype: string
  splits:
  - name: test
    num_bytes: 1632
    num_examples: 5
  download_size: 6961
  dataset_size: 1632
- config_name: code_technical_content_comments_across_languages
  features:
  - name: question
    dtype: string
  - name: choices
    sequence: string
  - name: answer
    dtype: int64
  - name: answer_label
    dtype: string
  - name: split
    dtype: string
  - name: subcategories
    dtype: string
  - name: lang
    dtype: string
  - name: second_lang
    dtype: string
  - name: coding_lang
    dtype: string
  - name: notes
    dtype: string
  - name: id
    dtype: string
  - name: set_id
    dtype: float64
  - name: variation_id
    dtype: string
  splits:
  - name: test
    num_bytes: 6024
    num_examples: 15
  download_size: 7966
  dataset_size: 6024
- config_name: code_technical_content_string_literals
  features:
  - name: question
    dtype: string
  - name: choices
    sequence: string
  - name: answer
    dtype: int64
  - name: answer_label
    dtype: string
  - name: split
    dtype: string
  - name: subcategories
    dtype: string
  - name: lang
    dtype: string
  - name: second_lang
    dtype: string
  - name: coding_lang
    dtype: string
  - name: notes
    dtype: string
  - name: id
    dtype: string
  - name: set_id
    dtype: float64
  - name: variation_id
    dtype: string
  splits:
  - name: test
    num_bytes: 3557
    num_examples: 10
  download_size: 6997
  dataset_size: 3557
- config_name: code_technical_content_syntax_and_punctuation_variations
  features:
  - name: question
    dtype: string
  - name: choices
    sequence: string
  - name: answer
    dtype: int64
  - name: answer_label
    dtype: string
  - name: split
    dtype: string
  - name: subcategories
    dtype: string
  - name: lang
    dtype: string
  - name: second_lang
    dtype: string
  - name: coding_lang
    dtype: string
  - name: notes
    dtype: string
  - name: id
    dtype: string
  - name: set_id
    dtype: float64
  - name: variation_id
    dtype: string
  splits:
  - name: test
    num_bytes: 5475
    num_examples: 16
  download_size: 7298
  dataset_size: 5475
- config_name: code_technical_content_variable_naming_conventions
  features:
  - name: question
    dtype: string
  - name: choices
    sequence: string
  - name: answer
    dtype: int64
  - name: answer_label
    dtype: string
  - name: split
    dtype: string
  - name: subcategories
    dtype: string
  - name: lang
    dtype: string
  - name: second_lang
    dtype: string
  - name: coding_lang
    dtype: string
  - name: notes
    dtype: string
  - name: id
    dtype: string
  - name: set_id
    dtype: float64
  - name: variation_id
    dtype: string
  splits:
  - name: test
    num_bytes: 5087
    num_examples: 12
  download_size: 7702
  dataset_size: 5087
- config_name: code_technical_content_whitespace_variations
  features:
  - name: question
    dtype: string
  - name: choices
    sequence: string
  - name: answer
    dtype: int64
  - name: answer_label
    dtype: string
  - name: split
    dtype: string
  - name: subcategories
    dtype: string
  - name: lang
    dtype: string
  - name: second_lang
    dtype: string
  - name: coding_lang
    dtype: string
  - name: notes
    dtype: string
  - name: id
    dtype: string
  - name: set_id
    dtype: float64
  - name: variation_id
    dtype: string
  splits:
  - name: test
    num_bytes: 5053
    num_examples: 15
  download_size: 7544
  dataset_size: 5053
configs:
- config_name: code_technical_content_buggy_code
  data_files:
  - split: test
    path: code_technical_content_buggy_code/test-*
- config_name: code_technical_content_cannonical
  data_files:
  - split: test
    path: code_technical_content_cannonical/test-*
- config_name: code_technical_content_comments_across_languages
  data_files:
  - split: test
    path: code_technical_content_comments_across_languages/test-*
- config_name: code_technical_content_string_literals
  data_files:
  - split: test
    path: code_technical_content_string_literals/test-*
- config_name: code_technical_content_syntax_and_punctuation_variations
  data_files:
  - split: test
    path: code_technical_content_syntax_and_punctuation_variations/test-*
- config_name: code_technical_content_variable_naming_conventions
  data_files:
  - split: test
    path: code_technical_content_variable_naming_conventions/test-*
- config_name: code_technical_content_whitespace_variations
  data_files:
  - split: test
    path: code_technical_content_whitespace_variations/test-*
---

# Dataset Card for Tokenization Robustness

<!-- Provide a quick summary of the dataset. -->

A comprehensive evaluation dataset for testing robustness of different tokenization strategies.

## Dataset Details

### Dataset Description

<!-- Provide a longer summary of what this dataset is. -->

This dataset evaluates how robust language models are to different tokenization strategies and edge cases. It includes questions with multiple choice answers designed to test various aspects of tokenization handling.

- **Curated by:** R3
- **Funded by [optional]:** [More Information Needed]
- **Shared by [optional]:** [More Information Needed]
- **Language(s) (NLP):** [More Information Needed]
- **License:** cc

### Dataset Sources [optional]

<!-- Provide the basic links for the dataset. -->

- **Repository:** [More Information Needed]
- **Paper [optional]:** [More Information Needed]
- **Demo [optional]:** [More Information Needed]

## Uses

<!-- Address questions around how the dataset is intended to be used. -->

### Direct Use

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[More Information Needed]

### Out-of-Scope Use

<!-- This section addresses misuse, malicious use, and uses that the dataset will not work well for. -->

[More Information Needed]

## Dataset Structure

<!-- This section provides a description of the dataset fields, and additional information about the dataset structure such as criteria used to create the splits, relationships between data points, etc. -->

The dataset contains multiple-choice questions with associated metadata about tokenization types and categories.

## Dataset Creation

### Curation Rationale

<!-- Motivation for the creation of this dataset. -->

[More Information Needed]

### Source Data

<!-- This section describes the source data (e.g. news text and headlines, social media posts, translated sentences, ...). -->

#### Data Collection and Processing

<!-- This section describes the data collection and processing process such as data selection criteria, filtering and normalization methods, tools and libraries used, etc. -->

[More Information Needed]

#### Who are the source data producers?

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### Annotations [optional]

<!-- If the dataset contains annotations which are not part of the initial data collection, use this section to describe them. -->

#### Annotation process

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#### Who are the annotators?

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#### Personal and Sensitive Information

<!-- State whether the dataset contains data that might be considered personal, sensitive, or private (e.g., data that reveals addresses, uniquely identifiable names or aliases, racial or ethnic origins, sexual orientations, religious beliefs, political opinions, financial or health data, etc.). If efforts were made to anonymize the data, describe the anonymization process. -->

[More Information Needed]

## Bias, Risks, and Limitations

<!-- This section is meant to convey both technical and sociotechnical limitations. -->

The dataset focuses primarily on English text and may not generalize to other languages or tokenization schemes not covered in the evaluation.

### Recommendations

<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->

Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.

## Citation [optional]

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**BibTeX:**

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**APA:**

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## Glossary [optional]

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## More Information [optional]

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## Dataset Card Authors [optional]

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## Dataset Card Contact

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