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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 |
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tags: |
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- multilingual |
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- tokenization |
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- robustness |
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dataset_info: |
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- config_name: tokenizer_robustness_completion_turkish_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 |
|
|
- name: subcategories |
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|
dtype: string |
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|
- name: categories |
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|
dtype: string |
|
|
- name: lang |
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|
dtype: string |
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|
- 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: |
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|
- name: CohereLabs/aya-expanse-8b |
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|
dtype: float64 |
|
|
- name: Qwen/Qwen3-8B |
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|
dtype: float64 |
|
|
- name: bigscience/bloom |
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|
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 |
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|
dtype: float64 |
|
|
- name: microsoft/Phi-3-mini-4k-instruct |
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|
dtype: float64 |
|
|
- name: mistralai/tekken |
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|
dtype: float64 |
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|
- name: tiktoken/gpt-4o |
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|
dtype: float64 |
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|
- name: tokenmonster/englishcode-32000-consistent-v1 |
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|
dtype: float64 |
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|
- name: trimmed_cos_sim_to_canonical |
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|
struct: |
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|
- 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 |
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|
dtype: float64 |
|
|
- name: facebook/xglm-564M |
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|
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 |
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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: 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 |
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|
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: 22368 |
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num_examples: 40 |
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download_size: 33264 |
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dataset_size: 22368 |
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- config_name: tokenizer_robustness_completion_turkish_code_language_script_switching |
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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: categories |
|
|
dtype: string |
|
|
- name: lang |
|
|
dtype: string |
|
|
- name: second_lang |
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|
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 |
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|
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 |
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|
num_bytes: 26317 |
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num_examples: 46 |
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download_size: 41715 |
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dataset_size: 26317 |
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- config_name: tokenizer_robustness_completion_turkish_colloquial |
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|
features: |
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|
- name: question |
|
|
dtype: string |
|
|
- 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: categories |
|
|
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: 20785 |
|
|
num_examples: 37 |
|
|
download_size: 39952 |
|
|
dataset_size: 20785 |
|
|
- config_name: tokenizer_robustness_completion_turkish_date_formats |
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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: categories |
|
|
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 |
|
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- 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: 20903 |
|
|
num_examples: 40 |
|
|
download_size: 39674 |
|
|
dataset_size: 20903 |
|
|
- config_name: tokenizer_robustness_completion_turkish_word_reordering |
|
|
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: categories |
|
|
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: 24484 |
|
|
num_examples: 44 |
|
|
download_size: 41126 |
|
|
dataset_size: 24484 |
|
|
configs: |
|
|
- config_name: tokenizer_robustness_completion_turkish_canonical |
|
|
data_files: |
|
|
- split: test |
|
|
path: tokenizer_robustness_completion_turkish_canonical/test-* |
|
|
- config_name: tokenizer_robustness_completion_turkish_code_language_script_switching |
|
|
data_files: |
|
|
- split: test |
|
|
path: >- |
|
|
tokenizer_robustness_completion_turkish_code_language_script_switching/test-* |
|
|
- config_name: tokenizer_robustness_completion_turkish_colloquial |
|
|
data_files: |
|
|
- split: test |
|
|
path: tokenizer_robustness_completion_turkish_colloquial/test-* |
|
|
- config_name: tokenizer_robustness_completion_turkish_date_formats |
|
|
data_files: |
|
|
- split: test |
|
|
path: tokenizer_robustness_completion_turkish_date_formats/test-* |
|
|
- config_name: tokenizer_robustness_completion_turkish_derivations |
|
|
data_files: |
|
|
- split: test |
|
|
path: tokenizer_robustness_completion_turkish_derivations/test-* |
|
|
- config_name: tokenizer_robustness_completion_turkish_dialects |
|
|
data_files: |
|
|
- split: test |
|
|
path: tokenizer_robustness_completion_turkish_dialects/test-* |
|
|
- config_name: tokenizer_robustness_completion_turkish_english_keyboard |
|
|
data_files: |
|
|
- split: test |
|
|
path: tokenizer_robustness_completion_turkish_english_keyboard/test-* |
|
|
- config_name: tokenizer_robustness_completion_turkish_equivalent_expressions |
|
|
data_files: |
|
|
- split: test |
|
|
path: tokenizer_robustness_completion_turkish_equivalent_expressions/test-* |
|
|
- config_name: tokenizer_robustness_completion_turkish_grammatical_errors |
|
|
data_files: |
|
|
- split: test |
|
|
path: tokenizer_robustness_completion_turkish_grammatical_errors/test-* |
|
|
- config_name: tokenizer_robustness_completion_turkish_inflections |
|
|
data_files: |
|
|
- split: test |
|
|
path: tokenizer_robustness_completion_turkish_inflections/test-* |
|
|
- config_name: tokenizer_robustness_completion_turkish_keyboard_proximity_errors |
|
|
data_files: |
|
|
- split: test |
|
|
path: tokenizer_robustness_completion_turkish_keyboard_proximity_errors/test-* |
|
|
- config_name: tokenizer_robustness_completion_turkish_orthographic_errors |
|
|
data_files: |
|
|
- split: test |
|
|
path: tokenizer_robustness_completion_turkish_orthographic_errors/test-* |
|
|
- config_name: tokenizer_robustness_completion_turkish_similar_words |
|
|
data_files: |
|
|
- split: test |
|
|
path: tokenizer_robustness_completion_turkish_similar_words/test-* |
|
|
- config_name: tokenizer_robustness_completion_turkish_spelled_out |
|
|
data_files: |
|
|
- split: test |
|
|
path: tokenizer_robustness_completion_turkish_spelled_out/test-* |
|
|
- config_name: tokenizer_robustness_completion_turkish_typographical_errors |
|
|
data_files: |
|
|
- split: test |
|
|
path: tokenizer_robustness_completion_turkish_typographical_errors/test-* |
|
|
- config_name: tokenizer_robustness_completion_turkish_web_search_query |
|
|
data_files: |
|
|
- split: test |
|
|
path: tokenizer_robustness_completion_turkish_web_search_query/test-* |
|
|
- config_name: tokenizer_robustness_completion_turkish_word_reordering |
|
|
data_files: |
|
|
- split: test |
|
|
path: tokenizer_robustness_completion_turkish_word_reordering/test-* |
|
|
language: |
|
|
- tr |
|
|
- en |
|
|
size_categories: |
|
|
- n<1K |
|
|
--- |
|
|
# Dataset Card for Tokenization Robustness |
|
|
|
|
|
<!-- 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 (Turkish Collection) |
|
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|
|
|
## Dataset Description |
|
|
|
|
|
This dataset is part of **TokSuite**, a comprehensive benchmark designed to measure how different tokenization strategies affect language model performance and robustness. This specific subset contains Turkish language multiple-choice text completion questions with various real-world perturbations that test tokenizer robustness. |
|
|
|
|
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- **Curated by:** R3 Research Team |
|
|
- **Language(s):** Turkish (Tr) |
|
|
- **License:** MIT License |
|
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|
|
|
### Dataset Summary |
|
|
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|
|
TokSuite addresses a fundamental challenge in language model research: understanding how tokenization choices impact model behavior in isolation. The Turkish subset specifically measures model performance on canonical questions and various perturbations. |
|
|
|
|
|
**Key Features:** |
|
|
- 40 canonical questions covering general knowledge, geography, science, and language understanding |
|
|
- Multiple perturbation types reflecting real-world text variations in Turkish |
|
|
- Parallel structure with TokSuite benchmark (available in English, Italian, Farsi, Chinese) |
|
|
- Native speaker curation ensuring linguistic authenticity |
|
|
|
|
|
### Supported Tasks |
|
|
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|
|
- **Multiple-Choice Question Answering**: Text completion format with 4 answer choices |
|
|
- **Tokenizer Robustness Evaluation**: Measuring performance degradation under various text perturbations |
|
|
- **Multilingual NLP Benchmarking**: Evaluating language models on Turkish text understanding |
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|
|
|
### Languages |
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|
|
The dataset contains text in Turkish (language code: `tur_Latn` / `tr`). |
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|
|
|
|
## Dataset Structure |
|
|
|
|
|
### Data Fields |
|
|
|
|
|
| Field | Type | Description | |
|
|
|-------|------|-------------| |
|
|
| `question` | `string` | The question text in Turkish | |
|
|
| `choices` | `list[string]` | 4 multiple-choice answer options | |
|
|
| `answer` | `int64` | Index of the correct answer | |
|
|
| `answer_label` | `string` | Letter label of the correct answer | |
|
|
| `split` | `string` | Dataset split identifier | |
|
|
| `subcategories` | `string` | Perturbation category | |
|
|
| `lang` | `string` | Language code | |
|
|
| `second_lang` | `string` | English translation or description of the question | |
|
|
| `notes` | `string` | Additional context about the question or perturbation | |
|
|
| `id` | `string` | Unique question identifier | |
|
|
| `set_id` | `float64` | Question set grouping identifier | |
|
|
| `variation_id` | `float64` | Variation number within a question set | |
|
|
| `vanilla_cos_sim_to_canonical` | `dict[string, float]` | Cosine similarity scores to canonical form (raw tokens) | |
|
|
| `trimmed_cos_sim_to_canonical` | `dict[string, float]` | Cosine similarity scores after token normalization | |
|
|
| `token_counts` | `dict[string, integer]` | Number of tokens produced per tokenizer | |
|
|
|
|
|
## Dataset Creation |
|
|
|
|
|
### Curation Rationale |
|
|
|
|
|
This dataset was created to: |
|
|
1. Systematically evaluate how different tokenization strategies handle Turkish |
|
|
2. Measure robustness against real-world text perturbations specific to Turkish |
|
|
3. Support research into the impact of tokenization on language model behavior |
|
|
4. Provide standardized benchmarks for Turkish language models |
|
|
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|
|
The questions were designed to be straightforward with high baseline accuracy, allowing researchers to cleanly measure performance degradation when perturbations are applied. |
|
|
|
|
|
### Source Data |
|
|
|
|
|
#### Data Collection and Processing |
|
|
|
|
|
- **Canonical Questions**: 40 baseline questions created in English |
|
|
- **Translation**: Native Turkish speakers translated questions |
|
|
- **Perturbations**: Each question underwent targeted perturbations designed to reflect Turkish characteristics |
|
|
- **Validation**: Model-in-the-loop process ensured high baseline accuracy |
|
|
|
|
|
#### Perturbation Categories |
|
|
|
|
|
1. **Canonical** |
|
|
The baseline Turkish text written in standard, grammatically correct Turkish with no perturbations. This serves as the reference condition for evaluating the impact of all other perturbations. |
|
|
|
|
|
2. **Abbreviations** |
|
|
Introduces common Turkish abbreviations and shortened forms (e.g., `Dr.`, `Prof.`, `vb.`, `sn.`), testing tokenizer robustness to compressed lexical forms. |
|
|
|
|
|
3. **Capitalization** |
|
|
Alters capitalization patterns by randomly capitalizing, lowercasing, or mixing case within words and sentences, simulating informal writing or casing errors. |
|
|
|
|
|
5. **Code / Language / Script Switching** |
|
|
Mixes Turkish with English words or phrases within the same sentence, reflecting real-world code-switching common in technical, academic, or online Turkish text. |
|
|
|
|
|
6. **Contractions** |
|
|
Applies contracted or fused forms common in informal Turkish writing (e.g., dropped vowels or merged suffix boundaries), stressing tokenizer handling of agglutinative morphology. |
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|
|
|
|
7. **Date Formats** |
|
|
Varies date representations (e.g., `12.03.2022`, `12 Mart 2022`, `03/12/22`), testing sensitivity to formatting and punctuation variation. |
|
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|
|
|
8. **Dialects** |
|
|
Introduces regional Turkish dialectal or colloquial variants that preserve meaning but differ lexically or morphologically from Standard Turkish. |
|
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|
|
|
9. **English Keyboard** |
|
|
Simulates Turkish text typed on an English keyboard, leading to missing or substituted Turkish-specific characters (e.g., `cok` instead of `çok`, `saglik` instead of `sağlık`). |
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|
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|
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10. **Grammatical Errors** |
|
|
Injects plausible grammatical mistakes such as incorrect suffix usage, agreement errors, or case marking issues, reflecting non-standard or learner Turkish. |
|
|
|
|
|
11. **Keyboard Proximity Errors** |
|
|
Introduces typos caused by pressing adjacent keys on a keyboard, simulating realistic typing errors without intentionally changing word choice. |
|
|
|
|
|
12. **Numerical Formats** |
|
|
Varies numeric representations (e.g., `1.000` vs. `1000`, comma vs. period usage for decimals), testing tokenizer sensitivity to locale-specific number formatting. |
|
|
|
|
|
13. **Orthographic Errors** |
|
|
Applies spelling mistakes that violate standard Turkish orthography (e.g., incorrect consonant usage or misspelled suffixes) while remaining plausible to native readers. |
|
|
|
|
|
14. **Phonetic Spelling** |
|
|
Replaces words with spellings based on pronunciation rather than standard orthography, reflecting informal or speech-inspired Turkish writing. |
|
|
|
|
|
15. **Plausible Diacritics Errors** |
|
|
Introduces missing, incorrect, or substituted diacritics (e.g., `s` vs. `ş`, `g` vs. `ğ`, `i` vs. `ı`), testing tokenizer sensitivity to Turkish-specific characters. |
|
|
|
|
|
16. **Similar Words** |
|
|
Substitutes words with closely related or easily confusable alternatives (e.g., near-synonyms or minimal lexical contrasts), preserving sentence plausibility. |
|
|
|
|
|
17. **Spelled-Out Forms** |
|
|
Replaces numerals, abbreviations, or symbols with fully spelled-out Turkish equivalents, increasing sequence length and altering token boundaries. |
|
|
|
|
|
18. **Typographical Errors** |
|
|
Introduces general typographical mistakes such as duplicated letters, missing characters, or minor corruption commonly found in fast or careless typing. |
|
|
|
|
|
19. **Web Search Query** |
|
|
Rewrites questions in the style of Turkish web search queries, using keyword-heavy phrasing, omitted function words, and informal structure typical of search engine inputs. |
|
|
|
|
|
#### Who are the source data producers? |
|
|
|
|
|
Native Turkish speakers curated and validated all questions and perturbations. The TokSuite research team at R3 designed the overall benchmark framework. |
|
|
|
|
|
### Annotations |
|
|
|
|
|
#### Annotation process |
|
|
|
|
|
Questions were manually created and translated by native speakers. Each perturbation was carefully designed to reflect authentic variations encountered in real-world Turkish text processing. |
|
|
|
|
|
#### Who are the annotators? |
|
|
|
|
|
Native Turkish speakers with expertise in linguistics and NLP, working as part of the TokSuite project. |
|
|
|
|
|
### Personal and Sensitive Information |
|
|
|
|
|
The dataset contains only general knowledge questions and does not include any personal or sensitive information. |
|
|
|
|
|
## Considerations for Using the Data |
|
|
|
|
|
### Social Impact of Dataset |
|
|
|
|
|
This dataset contributes to improving language technology for Turkish speakers by enabling better understanding of tokenization challenges and supporting more robust multilingual models. |
|
|
|
|
|
### Discussion of Biases |
|
|
|
|
|
- **Language variety**: he dataset uses Standard Turkish (Türkiye Türkçesi) and may not fully represent regional or dialectal variations. |
|
|
- **Script focus**: Only the Latin script is used; Turkish-specific diacritics and keyboard-related variations are included as perturbations. |
|
|
- **Domain coverage**: Questions focus on general knowledge and may not represent domain-specific Turkish language use. |
|
|
- **Question simplicity**: Designed for high baseline accuracy, which may not reflect real-world task complexity. |
|
|
|
|
|
### Other Known Limitations |
|
|
|
|
|
- Relatively small dataset size (evaluation-only) |
|
|
- Multiple-choice format |
|
|
- Language-specific perturbations |
|
|
- Results may differ at larger model scales |
|
|
|
|
|
## Additional Information |
|
|
|
|
|
### Dataset Curators |
|
|
|
|
|
The dataset was curated by the TokSuite research team at R3. |
|
|
|
|
|
### Licensing Information |
|
|
|
|
|
MIT license |
|
|
|
|
|
### 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}, |
|
|
booktitle={Preprint.}, |
|
|
year={2026}, |
|
|
arxiv={https://arxiv.org/abs/2512.20757}, |
|
|
url={TBD} |
|
|
} |
|
|
``` |
|
|
|
|
|
**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 |
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- Multilingual benchmark datasets (English, Turkish, Italian, Farsi, Chinese) |
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- Comprehensive analysis of tokenization's impact on model behavior |
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### Contact |
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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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--- |
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<div align="center"> |
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**Part of the [TokSuite Project](TBD)** |
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*Understanding Tokenization's Role in Language Model Behavior* |
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</div> |
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