Datasets:

r-three
/

tokenizer_robustness_completion_math

license: cc
multilinguality: multilingual
task_categories:
  - multiple-choice
pretty_name: Tokenization Robustness Math
tags:
  - multilingual
  - tokenization
dataset_info:
  - config_name: tokenizer_robustness_completion_math_canonical
    features:
      - name: question
        dtype: string
      - name: choices
        list: string
      - name: answer
        dtype: int64
      - name: answer_label
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      - name: subcategories
        dtype: string
      - name: category
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      - name: lang
        dtype: string
      - name: second_lang
        dtype: string
      - name: notes
        dtype: string
      - name: id
        dtype: string
      - name: set_id
        dtype: string
      - name: variation_id
        dtype: string
      - name: vanilla_cos_sim_to_canonical
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          - name: tokenmonster/englishcode-32000-consistent-v1
            dtype: float64
      - name: trimmed_cos_sim_to_canonical
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          - name: mistralai/tekken
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          - name: tiktoken/gpt-4o
            dtype: float64
          - name: tokenmonster/englishcode-32000-consistent-v1
            dtype: float64
      - name: token_counts
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          - name: gpt2
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          - name: microsoft/Phi-3-mini-4k-instruct
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          - name: mistralai/tekken
            dtype: int64
          - name: tiktoken/gpt-4o
            dtype: int64
          - name: tokenmonster/englishcode-32000-consistent-v1
            dtype: int64
    splits:
      - name: test
        num_bytes: 11202
        num_examples: 21
    download_size: 29976
    dataset_size: 11202
  - config_name: tokenizer_robustness_completion_math_chinese
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      - name: choices
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      - name: lang
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      - name: second_lang
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      - name: id
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      - name: set_id
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          - name: microsoft/Phi-3-mini-4k-instruct
            dtype: int64
          - name: mistralai/tekken
            dtype: int64
          - name: tiktoken/gpt-4o
            dtype: int64
          - name: tokenmonster/englishcode-32000-consistent-v1
            dtype: int64
    splits:
      - name: test
        num_bytes: 11147
        num_examples: 21
    download_size: 34445
    dataset_size: 11147
  - config_name: tokenizer_robustness_completion_math_decorative_unicode
    features:
      - name: question
        dtype: string
      - name: choices
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      - name: answer
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      - name: answer_label
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      - name: subcategories
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      - name: category
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      - name: lang
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      - name: second_lang
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      - name: notes
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          - name: tiktoken/gpt-4o
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    splits:
      - name: test
        num_bytes: 11986
        num_examples: 21
    download_size: 34660
    dataset_size: 11986
  - config_name: tokenizer_robustness_completion_math_farsi
    features:
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      - name: choices
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          - name: tiktoken/gpt-4o
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          - name: tokenmonster/englishcode-32000-consistent-v1
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      - name: token_counts
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            dtype: int64
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          - name: tokenmonster/englishcode-32000-consistent-v1
            dtype: int64
    splits:
      - name: test
        num_bytes: 12034
        num_examples: 21
    download_size: 34859
    dataset_size: 12034
  - config_name: tokenizer_robustness_completion_math_italian
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          - name: tiktoken/gpt-4o
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    splits:
      - name: test
        num_bytes: 11219
        num_examples: 21
    download_size: 34631
    dataset_size: 11219
  - config_name: tokenizer_robustness_completion_math_latex
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      - name: token_counts
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            dtype: int64
          - name: tiktoken/gpt-4o
            dtype: int64
          - name: tokenmonster/englishcode-32000-consistent-v1
            dtype: int64
    splits:
      - name: test
        num_bytes: 11494
        num_examples: 21
    download_size: 34230
    dataset_size: 11494
  - config_name: tokenizer_robustness_completion_math_space_removal
    features:
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          - name: Qwen/Qwen3-8B
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          - name: microsoft/Phi-3-mini-4k-instruct
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          - name: tokenmonster/englishcode-32000-consistent-v1
            dtype: float64
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          - name: facebook/xglm-564M
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          - name: google/gemma-2-2b
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          - name: gpt2
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          - name: microsoft/Phi-3-mini-4k-instruct
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          - name: tiktoken/gpt-4o
            dtype: float64
          - name: tokenmonster/englishcode-32000-consistent-v1
            dtype: float64
      - name: token_counts
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          - name: CohereLabs/aya-expanse-8b
            dtype: int64
          - name: Qwen/Qwen3-8B
            dtype: int64
          - name: bigscience/bloom
            dtype: int64
          - name: common-pile/comma-v0.1-1t
            dtype: int64
          - name: facebook/xglm-564M
            dtype: int64
          - name: google-bert/bert-base-multilingual-cased
            dtype: int64
          - name: google/byt5-small
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          - name: google/gemma-2-2b
            dtype: int64
          - name: gpt2
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          - name: meta-llama/Llama-3.2-1B
            dtype: int64
          - name: microsoft/Phi-3-mini-4k-instruct
            dtype: int64
          - name: mistralai/tekken
            dtype: int64
          - name: tiktoken/gpt-4o
            dtype: int64
          - name: tokenmonster/englishcode-32000-consistent-v1
            dtype: int64
    splits:
      - name: test
        num_bytes: 11559
        num_examples: 21
    download_size: 34064
    dataset_size: 11559
  - config_name: tokenizer_robustness_completion_math_spelled_out
    features:
      - name: question
        dtype: string
      - name: choices
        list: string
      - name: answer
        dtype: int64
      - name: answer_label
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      - name: split
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      - name: subcategories
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      - name: category
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      - name: lang
        dtype: string
      - name: second_lang
        dtype: string
      - name: notes
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      - name: id
        dtype: string
      - name: set_id
        dtype: string
      - name: variation_id
        dtype: string
      - name: vanilla_cos_sim_to_canonical
        struct:
          - name: CohereLabs/aya-expanse-8b
            dtype: float64
          - name: Qwen/Qwen3-8B
            dtype: float64
          - name: bigscience/bloom
            dtype: float64
          - name: common-pile/comma-v0.1-1t
            dtype: float64
          - name: facebook/xglm-564M
            dtype: float64
          - name: google-bert/bert-base-multilingual-cased
            dtype: float64
          - name: google/byt5-small
            dtype: float64
          - name: google/gemma-2-2b
            dtype: float64
          - name: gpt2
            dtype: float64
          - name: meta-llama/Llama-3.2-1B
            dtype: float64
          - name: microsoft/Phi-3-mini-4k-instruct
            dtype: float64
          - name: mistralai/tekken
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          - name: tiktoken/gpt-4o
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          - name: tokenmonster/englishcode-32000-consistent-v1
            dtype: float64
      - name: trimmed_cos_sim_to_canonical
        struct:
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            dtype: float64
          - name: Qwen/Qwen3-8B
            dtype: float64
          - name: bigscience/bloom
            dtype: float64
          - name: common-pile/comma-v0.1-1t
            dtype: float64
          - name: facebook/xglm-564M
            dtype: float64
          - name: google-bert/bert-base-multilingual-cased
            dtype: float64
          - name: google/byt5-small
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          - name: google/gemma-2-2b
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          - name: gpt2
            dtype: float64
          - name: meta-llama/Llama-3.2-1B
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          - name: microsoft/Phi-3-mini-4k-instruct
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          - name: tiktoken/gpt-4o
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          - name: tokenmonster/englishcode-32000-consistent-v1
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      - name: token_counts
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            dtype: int64
          - name: Qwen/Qwen3-8B
            dtype: int64
          - name: bigscience/bloom
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          - name: common-pile/comma-v0.1-1t
            dtype: int64
          - name: facebook/xglm-564M
            dtype: int64
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            dtype: int64
          - name: google/byt5-small
            dtype: int64
          - name: google/gemma-2-2b
            dtype: int64
          - name: gpt2
            dtype: int64
          - name: meta-llama/Llama-3.2-1B
            dtype: int64
          - name: microsoft/Phi-3-mini-4k-instruct
            dtype: int64
          - name: mistralai/tekken
            dtype: int64
          - name: tiktoken/gpt-4o
            dtype: int64
          - name: tokenmonster/englishcode-32000-consistent-v1
            dtype: int64
    splits:
      - name: test
        num_bytes: 12129
        num_examples: 21
    download_size: 34634
    dataset_size: 12129
  - config_name: tokenizer_robustness_completion_math_turkish
    features:
      - name: question
        dtype: string
      - name: choices
        list: string
      - name: answer
        dtype: int64
      - name: answer_label
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      - name: split
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      - name: subcategories
        dtype: string
      - name: category
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      - name: lang
        dtype: string
      - name: second_lang
        dtype: string
      - name: notes
        dtype: string
      - name: id
        dtype: string
      - name: set_id
        dtype: string
      - name: variation_id
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          - name: common-pile/comma-v0.1-1t
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            dtype: float64
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          - name: google/gemma-2-2b
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          - name: gpt2
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          - name: tiktoken/gpt-4o
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          - name: tokenmonster/englishcode-32000-consistent-v1
            dtype: float64
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            dtype: int64
          - name: microsoft/Phi-3-mini-4k-instruct
            dtype: int64
          - name: mistralai/tekken
            dtype: int64
          - name: tiktoken/gpt-4o
            dtype: int64
          - name: tokenmonster/englishcode-32000-consistent-v1
            dtype: int64
    splits:
      - name: test
        num_bytes: 11339
        num_examples: 21
    download_size: 34650
    dataset_size: 11339
configs:
  - config_name: tokenizer_robustness_completion_math_canonical
    data_files:
      - split: test
        path: tokenizer_robustness_completion_math_canonical/test-*
  - config_name: tokenizer_robustness_completion_math_chinese
    data_files:
      - split: test
        path: tokenizer_robustness_completion_math_chinese/test-*
  - config_name: tokenizer_robustness_completion_math_decorative_unicode
    data_files:
      - split: test
        path: tokenizer_robustness_completion_math_decorative_unicode/test-*
  - config_name: tokenizer_robustness_completion_math_farsi
    data_files:
      - split: test
        path: tokenizer_robustness_completion_math_farsi/test-*
  - config_name: tokenizer_robustness_completion_math_italian
    data_files:
      - split: test
        path: tokenizer_robustness_completion_math_italian/test-*
  - config_name: tokenizer_robustness_completion_math_latex
    data_files:
      - split: test
        path: tokenizer_robustness_completion_math_latex/test-*
  - config_name: tokenizer_robustness_completion_math_space_removal
    data_files:
      - split: test
        path: tokenizer_robustness_completion_math_space_removal/test-*
  - config_name: tokenizer_robustness_completion_math_spelled_out
    data_files:
      - split: test
        path: tokenizer_robustness_completion_math_spelled_out/test-*
  - config_name: tokenizer_robustness_completion_math_turkish
    data_files:
      - split: test
        path: tokenizer_robustness_completion_math_turkish/test-*
Dataset Card for Tokenization Robustness Math

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

Dataset Description

This dataset evaluates how robust language models are to different tokenization strategies and edge cases. It includes text completion questions with multiple choice answers designed to test various aspects of tokenization handling.
Curated by: R3
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Shared by [optional]: [More Information Needed]
Language(s) (NLP): [More Information Needed]
License: cc
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Uses

Direct Use

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Out-of-Scope Use

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Dataset Structure

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

Curation Rationale

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Source Data

Data Collection and Processing

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Annotation process

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Personal and Sensitive Information

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Bias, Risks, and Limitations

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

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