Datasets:
metadata
license: cc
multilinguality: multilingual
task_categories:
- multiple-choice
pretty_name: Tokenization Robustness
tags:
- multilingual
- tokenization
dataset_info:
- config_name: tokenizer_robustness_completion_stem_canonical
features:
- name: question
dtype: string
- name: choices
list: 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: notes
dtype: string
- name: id
dtype: string
- name: set_id
dtype: string
- name: variation_id
dtype: string
- name: question_general_category
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
dtype: float64
- name: tiktoken/gpt-4o
dtype: float64
- 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
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
dtype: float64
- name: tiktoken/gpt-4o
dtype: float64
- name: tokenmonster/englishcode-32000-consistent-v1
dtype: float64
- name: token_counts
struct:
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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
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: 23517
num_examples: 44
download_size: 32406
dataset_size: 23517
- config_name: tokenizer_robustness_completion_stem_character_deletion
features:
- name: question
dtype: string
- name: choices
list: string
- name: answer
dtype: int64
- name: answer_label
dtype: string
- name: split
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- name: subcategories
dtype: string
- 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: question_general_category
dtype: string
- name: vanilla_cos_sim_to_canonical
struct:
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- name: tiktoken/gpt-4o
dtype: float64
- name: tokenmonster/englishcode-32000-consistent-v1
dtype: float64
- name: trimmed_cos_sim_to_canonical
struct:
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- name: gpt2
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- name: tiktoken/gpt-4o
dtype: float64
- name: tokenmonster/englishcode-32000-consistent-v1
dtype: float64
- name: token_counts
struct:
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- name: microsoft/Phi-3-mini-4k-instruct
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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: 22723
num_examples: 41
download_size: 40680
dataset_size: 22723
- config_name: tokenizer_robustness_completion_stem_colloquial
features:
- name: question
dtype: string
- name: choices
list: string
- name: answer
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- name: answer_label
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- name: lang
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- name: second_lang
dtype: string
- name: notes
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- name: set_id
dtype: string
- name: variation_id
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- name: question_general_category
dtype: string
- name: vanilla_cos_sim_to_canonical
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- name: tiktoken/gpt-4o
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- name: tokenmonster/englishcode-32000-consistent-v1
dtype: float64
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struct:
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- name: mistralai/tekken
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- name: tiktoken/gpt-4o
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- name: tokenmonster/englishcode-32000-consistent-v1
dtype: int64
splits:
- name: test
num_bytes: 7820
num_examples: 15
download_size: 32313
dataset_size: 7820
- config_name: tokenizer_robustness_completion_stem_compounds
features:
- name: question
dtype: string
- name: choices
list: string
- name: answer
dtype: int64
- name: answer_label
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- name: vanilla_cos_sim_to_canonical
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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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- name: Qwen/Qwen3-8B
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- name: tokenmonster/englishcode-32000-consistent-v1
dtype: int64
splits:
- name: test
num_bytes: 566
num_examples: 1
download_size: 27881
dataset_size: 566
- config_name: tokenizer_robustness_completion_stem_diacriticized_styling
features:
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dtype: string
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splits:
- name: test
num_bytes: 32623
num_examples: 55
download_size: 33837
dataset_size: 32623
- config_name: tokenizer_robustness_completion_stem_double_struck
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splits:
- name: test
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num_examples: 18
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dataset_size: 11237
- config_name: tokenizer_robustness_completion_stem_enclosed_characters
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- config_name: tokenizer_robustness_completion_stem_double_struck
data_files:
- split: test
path: tokenizer_robustness_completion_stem_double_struck/test-*
- config_name: tokenizer_robustness_completion_stem_enclosed_characters
data_files:
- split: test
path: tokenizer_robustness_completion_stem_enclosed_characters/test-*
- config_name: tokenizer_robustness_completion_stem_equivalent_expressions
data_files:
- split: test
path: tokenizer_robustness_completion_stem_equivalent_expressions/test-*
- config_name: tokenizer_robustness_completion_stem_fullwidth_characters
data_files:
- split: test
path: tokenizer_robustness_completion_stem_fullwidth_characters/test-*
- config_name: tokenizer_robustness_completion_stem_latex
data_files:
- split: test
path: tokenizer_robustness_completion_stem_latex/test-*
- config_name: tokenizer_robustness_completion_stem_morpheme_separation
data_files:
- split: test
path: tokenizer_robustness_completion_stem_morpheme_separation/test-*
- config_name: tokenizer_robustness_completion_stem_scripted_text
data_files:
- split: test
path: tokenizer_robustness_completion_stem_scripted_text/test-*
- config_name: tokenizer_robustness_completion_stem_space_removal
data_files:
- split: test
path: tokenizer_robustness_completion_stem_space_removal/test-*
- config_name: tokenizer_robustness_completion_stem_spelled_out
data_files:
- split: test
path: tokenizer_robustness_completion_stem_spelled_out/test-*
- config_name: tokenizer_robustness_completion_stem_strikethrough
data_files:
- split: test
path: tokenizer_robustness_completion_stem_strikethrough/test-*
- config_name: tokenizer_robustness_completion_stem_superscript_subscript
data_files:
- split: test
path: tokenizer_robustness_completion_stem_superscript_subscript/test-*
- config_name: tokenizer_robustness_completion_stem_typographical_errors
data_files:
- split: test
path: tokenizer_robustness_completion_stem_typographical_errors/test-*
- config_name: tokenizer_robustness_completion_stem_unicode_formatting
data_files:
- split: test
path: tokenizer_robustness_completion_stem_unicode_formatting/test-*
- config_name: tokenizer_robustness_completion_stem_unusual_formatting
data_files:
- split: test
path: tokenizer_robustness_completion_stem_unusual_formatting/test-*
- config_name: tokenizer_robustness_completion_stem_upside_down_rotated
data_files:
- split: test
path: tokenizer_robustness_completion_stem_upside_down_rotated/test-*
Dataset Card for Tokenization Robustness
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
- Funded by [optional]: [More Information Needed]
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- Language(s) (NLP): [More Information Needed]
- License: cc
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Uses
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Dataset Structure
The dataset contains multiple-choice questions with associated metadata about tokenization types and categories.
Dataset Creation
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Source Data
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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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