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--- |
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license: mit |
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multilinguality: multilingual |
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task_categories: |
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- multiple-choice |
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pretty_name: Tokenization Robustness Math |
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tags: |
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- tokenization |
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- mathematics |
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dataset_info: |
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- config_name: tokenizer_robustness_completion_math_canonical |
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features: |
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|
- name: question |
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|
dtype: string |
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|
- name: choices |
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|
list: string |
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|
- name: answer |
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|
dtype: int64 |
|
|
- name: answer_label |
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|
dtype: string |
|
|
- name: split |
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|
dtype: string |
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|
- name: subcategories |
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|
dtype: string |
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|
- name: category |
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|
dtype: string |
|
|
- name: lang |
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|
dtype: string |
|
|
- name: second_lang |
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|
dtype: string |
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|
- name: notes |
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|
dtype: string |
|
|
- name: id |
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|
dtype: string |
|
|
- name: set_id |
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|
dtype: string |
|
|
- name: variation_id |
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|
dtype: string |
|
|
- name: vanilla_cos_sim_to_canonical |
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|
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 |
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|
dtype: float64 |
|
|
- name: facebook/xglm-564M |
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|
dtype: float64 |
|
|
- name: google-bert/bert-base-multilingual-cased |
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|
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 |
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|
dtype: float64 |
|
|
- name: mistralai/tekken |
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|
dtype: float64 |
|
|
- name: tiktoken/gpt-4o |
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|
dtype: float64 |
|
|
- name: tokenmonster/englishcode-32000-consistent-v1 |
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|
dtype: float64 |
|
|
- name: trimmed_cos_sim_to_canonical |
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|
struct: |
|
|
- name: CohereLabs/aya-expanse-8b |
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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 |
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|
dtype: float64 |
|
|
- name: mistralai/tekken |
|
|
dtype: float64 |
|
|
- name: tiktoken/gpt-4o |
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|
dtype: float64 |
|
|
- name: tokenmonster/englishcode-32000-consistent-v1 |
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|
dtype: float64 |
|
|
- name: token_counts |
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|
struct: |
|
|
- 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 |
|
|
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 |
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|
dtype: int64 |
|
|
- name: tiktoken/gpt-4o |
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|
dtype: int64 |
|
|
- name: tokenmonster/englishcode-32000-consistent-v1 |
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|
dtype: int64 |
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|
splits: |
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|
- name: test |
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num_bytes: 11202 |
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num_examples: 21 |
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download_size: 29976 |
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dataset_size: 11202 |
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- config_name: tokenizer_robustness_completion_math_chinese |
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features: |
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- name: question |
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|
dtype: string |
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|
- name: choices |
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|
list: string |
|
|
- name: answer |
|
|
dtype: int64 |
|
|
- name: answer_label |
|
|
dtype: string |
|
|
- name: split |
|
|
dtype: string |
|
|
- name: subcategories |
|
|
dtype: string |
|
|
- name: category |
|
|
dtype: string |
|
|
- name: lang |
|
|
dtype: string |
|
|
- name: second_lang |
|
|
dtype: string |
|
|
- name: notes |
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|
dtype: string |
|
|
- name: id |
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|
dtype: string |
|
|
- name: set_id |
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|
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 |
|
|
dtype: float64 |
|
|
- name: tiktoken/gpt-4o |
|
|
dtype: float64 |
|
|
- name: tokenmonster/englishcode-32000-consistent-v1 |
|
|
dtype: float64 |
|
|
- name: trimmed_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: token_counts |
|
|
struct: |
|
|
- 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 |
|
|
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: 11147 |
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num_examples: 21 |
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download_size: 34445 |
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dataset_size: 11147 |
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|
- config_name: tokenizer_robustness_completion_math_decorative_unicode |
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|
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: category |
|
|
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: 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: |
|
|
- 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: token_counts |
|
|
struct: |
|
|
- 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 |
|
|
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: 11986 |
|
|
num_examples: 21 |
|
|
download_size: 34660 |
|
|
dataset_size: 11986 |
|
|
- config_name: tokenizer_robustness_completion_math_farsi |
|
|
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: category |
|
|
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: 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: |
|
|
- 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: token_counts |
|
|
struct: |
|
|
- 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 |
|
|
dtype: int64 |
|
|
- name: google/gemma-2-2b |
|
|
dtype: int64 |
|
|
- name: gpt2 |
|
|
dtype: int64 |
|
|
- name: meta-llama/Llama-3.2-1B |
|
|
dtype: int64 |
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- 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 |
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|
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: category |
|
|
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: 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: |
|
|
- 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: token_counts |
|
|
struct: |
|
|
- 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 |
|
|
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: 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-* |
|
|
language: |
|
|
- en |
|
|
- fa |
|
|
- zh |
|
|
- it |
|
|
- tr |
|
|
size_categories: |
|
|
- n<1K |
|
|
--- |
|
|
# Dataset Card for Tokenization Robustness (Math) |
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|
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<!-- Provide a quick summary of the dataset. --> |
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<img src="toksuite-logo.png" alt="TokSuite Logo" width="250px" style="margin-left:'auto' margin-right:'auto' display:'block'"/> |
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# TokSuite Benchmark (Math Collection) |
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## Dataset Description |
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This dataset is part of **TokSuite**, a comprehensive benchmark designed to measure how different tokenization strategies affect language model behavior under controlled conditions. |
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This specific subset focuses on **mathematical text completion**, containing multiple-choice math questions with a variety of **surface-form perturbations** that stress tokenizer handling of numbers, symbols, formatting, scripts, and mathematical notation. |
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- **Curated by:** R3 Research Team |
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- **Domain:** Mathematics |
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- **License:** MIT License |
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### Dataset Summary |
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TokSuite isolates the impact of tokenization by holding **model architecture, training data, training budget, and initialization constant**, varying only the tokenizer. |
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The Math benchmark evaluates performance on: |
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- A **canonical mathematical formulation** |
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- Multiple **perturbed variants** that preserve mathematical meaning while altering surface representation |
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These perturbations reflect realistic variation in how mathematical expressions are written, formatted, localized, and queried in practice. |
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**Key Features:** |
|
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- 21 canonical math questions with unambiguous answers |
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- Perturbations targeting notation, symbols, scripts, and formatting |
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- Parallel structure with TokSuite language benchmarks |
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- Designed for **evaluation**, not training |
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### Supported Tasks |
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- **Multiple-Choice Math Question Answering** |
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- **Tokenizer Robustness Evaluation** |
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- **Symbolic and Numerical Text Processing** |
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|
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|
--- |
|
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|
## Dataset Structure |
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### Data Fields |
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|
|
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| Field | Type | Description | |
|
|
|------|------|-------------| |
|
|
| `question` | `string` | Mathematical question text | |
|
|
| `choices` | `list[string]` | Multiple-choice answer options | |
|
|
| `answer` | `int64` | Index of the correct answer | |
|
|
| `answer_label` | `string` | Letter label of the correct answer | |
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|
| `split` | `string` | Dataset split identifier (all entries are `test`) | |
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|
| `subcategories` | `string` | Perturbation category | |
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| `lang` | `string` | Domain identifier (`math`) | |
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| `second_lang` | `string` | English translation or description of the question | |
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| `notes` | `string` | Additional context about the perturbation | |
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| `id` | `string` | Unique question identifier | |
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|
| `set_id` | `float64` | Question set grouping identifier | |
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| `variation_id` | `float64` | Variation number within a question set | |
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| `vanilla_cos_sim_to_canonical` | `dict[string, float]` | Cosine similarity to canonical form using raw token sequences | |
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| `trimmed_cos_sim_to_canonical` | `dict[string, float]` | Cosine similarity after token normalization | |
|
|
| `token_counts` | `dict[string, int]` | Number of tokens produced per tokenizer | |
|
|
|
|
|
--- |
|
|
|
|
|
## Dataset Creation |
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### Curation Rationale |
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This dataset was created to: |
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|
1. Systematically evaluate tokenizer robustness on **mathematical notation and structure** |
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2. Measure sensitivity to changes in formatting, symbols, scripts, and numeric representation |
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3. Isolate tokenization effects from mathematical reasoning difficulty |
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4. Provide standardized benchmarks for math-focused language models |
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Canonical questions are intentionally **simple and high-accuracy**, allowing researchers to attribute performance degradation to tokenization rather than reasoning complexity. |
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### Source Data |
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|
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- Canonical math questions were manually authored |
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- Each question was perturbed while preserving mathematical equivalence |
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- Canonical accuracy was validated across TokSuite models |
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|
--- |
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## Perturbation Categories (Math) |
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1. **Canonical** |
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The baseline mathematical text written in a standard, well-formatted form with no perturbations. This serves as the reference condition for evaluating all other perturbations. |
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2. **Chinese** |
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Rewrites mathematical text using Chinese characters for numbers, operators, or surrounding descriptions, testing tokenizer robustness to non-Latin scripts in math contexts. |
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3. **Decorative Unicode** |
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Replaces standard mathematical symbols with visually similar decorative or stylized Unicode characters (e.g., fancy numerals or operators), stressing Unicode normalization and symbol handling. |
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4. **Farsi** |
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Introduces Persian (Farsi) numerals or script elements into mathematical expressions, testing tokenizer robustness to right-to-left scripts and cross-script numeric representations. |
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5. **Italian** |
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Rewrites textual components of math problems in Italian while preserving the same mathematical structure and solution. |
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6. **LaTeX** |
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Encodes mathematical expressions using LaTeX-style syntax (e.g., `\frac`, `^`, `_`), stressing tokenizer handling of markup-heavy mathematical notation. |
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7. **Space Removal** |
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Removes or alters spacing within mathematical expressions and surrounding text, stressing tokenizer assumptions about whitespace in math contexts. |
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8. **Spelled-Out Forms** |
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Replaces numerals or symbols with fully spelled-out textual equivalents (e.g., numbers written as words), increasing sequence length and altering token boundaries. |
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9. **Turkish** |
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Rewrites textual components of math problems in Turkish while preserving the underlying mathematical meaning. |
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|
--- |
|
|
|
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## Considerations for Using the Data |
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|
|
- **Language variety:** The dataset uses standard mathematical notation and English-language math phrasing, and may not represent informal or pedagogical math language. |
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|
- **Script focus:** Mathematical expressions are primarily written using ASCII and standard Unicode; LaTeX, decorative Unicode, and non-Latin scripts are included as perturbations. |
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|
- **Domain coverage:** Questions focus on general mathematics and may not represent highly specialized or advanced mathematical domains. |
|
|
- **Question simplicity:** Designed for high baseline accuracy, which may not reflect real-world mathematical task complexity. |
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|
|
|
|
--- |
|
|
|
|
|
## Additional Information |
|
|
|
|
|
### Dataset Curators |
|
|
|
|
|
The dataset was curated by the TokSuite research team at R3. |
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|
|
|
### Licensing Information |
|
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|
|
MIT License |
|
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|
|
|
### Citation Information |
|
|
|
|
|
If you use this dataset in your research, please cite the TokSuite paper: |
|
|
|
|
|
```bibtex |
|
|
@inproceedings{toksuite2026, |
|
|
title={TokSuite: Measuring the Impact of Tokenizer Choice on Language Model Behavior}, |
|
|
author={Altıntaş, Gül Sena and Ehghaghi, Malikeh and Lester, Brian and Liu, Fengyuan and Zhao, Wanru and Ciccone, Marco and Raffel, Colin}, |
|
|
year={2026}, |
|
|
arxiv={https://arxiv.org/abs/2512.20757}, |
|
|
} |
|
|
``` |
|
|
|
|
|
**Paper**: [TokSuite: Measuring the Impact of Tokenizer Choice on Language Model Behavior](TBD) |
|
|
|
|
|
### Contributions |
|
|
|
|
|
This dataset is part of TokSuite, which includes: |
|
|
- 14 language models with identical architectures but different tokenizers |
|
|
- Multilingual benchmark datasets (English, Turkish, Italian, Farsi, Chinese) |
|
|
- Comprehensive analysis of tokenization's impact on model behavior |
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|
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|
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|
|
### Contact |
|
|
|
|
|
For questions or issues related to this dataset, please refer to the TokSuite project or contact the authors of the paper. |
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|
|
|
|
--- |
|
|
|
|
|
<div align="center"> |
|
|
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|
|
**Part of the [TokSuite Project](TBD)** |
|
|
|
|
|
*Understanding Tokenization's Role in Language Model Behavior* |
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|
|
|
|
</div> |
