Datasets:
metadata
license: mit
multilinguality: multilingual
task_categories:
- multiple-choice
pretty_name: Tokenization Robustness
tags:
- multilingual
- tokenization
- robustness
dataset_info:
- config_name: tokenizer_robustness_completion_italian_abbreviations
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: perturbed_word
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: 15662
num_examples: 27
download_size: 34752
dataset_size: 15662
- config_name: tokenizer_robustness_completion_italian_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: 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: perturbed_word
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: 22185
num_examples: 40
download_size: 33668
dataset_size: 22185
- config_name: tokenizer_robustness_completion_italian_capitalization
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: perturbed_word
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: 4891
num_examples: 9
download_size: 30739
dataset_size: 4891
- config_name: tokenizer_robustness_completion_italian_code_language_script_switching
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: perturbed_word
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: 21915
num_examples: 39
download_size: 40662
dataset_size: 21915
- config_name: tokenizer_robustness_completion_italian_contractions
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: perturbed_word
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: 12086
num_examples: 21
download_size: 33858
dataset_size: 12086
- config_name: tokenizer_robustness_completion_italian_date_formats
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: perturbed_word
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: 3452
num_examples: 6
download_size: 29387
dataset_size: 3452
- config_name: tokenizer_robustness_completion_italian_dialects
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: perturbed_word
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: 16359
num_examples: 31
download_size: 35120
dataset_size: 16359
- config_name: tokenizer_robustness_completion_italian_english_keyboard
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: perturbed_word
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: 36901
num_examples: 68
download_size: 41589
dataset_size: 36901
- config_name: tokenizer_robustness_completion_italian_grammatical_errors
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: perturbed_word
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: 49702
num_examples: 86
download_size: 49167
dataset_size: 49702
- config_name: tokenizer_robustness_completion_italian_keyboard_proximity_errors
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: perturbed_word
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: 124868
num_examples: 231
download_size: 82243
dataset_size: 124868
- config_name: tokenizer_robustness_completion_italian_numerical_formats
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: perturbed_word
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: 5005
num_examples: 8
download_size: 29952
dataset_size: 5005
- config_name: tokenizer_robustness_completion_italian_orthographic_errors
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: perturbed_word
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: 54975
num_examples: 92
download_size: 52569
dataset_size: 54975
- config_name: tokenizer_robustness_completion_italian_phonetic_spelling
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: perturbed_word
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: 24151
num_examples: 43
download_size: 39932
dataset_size: 24151
- config_name: tokenizer_robustness_completion_italian_plausible_diacritics_errors
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: perturbed_word
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: 9256
num_examples: 17
download_size: 32230
dataset_size: 9256
- config_name: tokenizer_robustness_completion_italian_similar_words
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: perturbed_word
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: 6752
num_examples: 12
download_size: 31786
dataset_size: 6752
- config_name: tokenizer_robustness_completion_italian_spelled_out
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: perturbed_word
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: 20098
num_examples: 37
download_size: 35213
dataset_size: 20098
- config_name: tokenizer_robustness_completion_italian_typographical_errors
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: perturbed_word
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: 158477
num_examples: 281
download_size: 89075
dataset_size: 158477
- config_name: tokenizer_robustness_completion_italian_web_search_query
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: perturbed_word
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: 20426
num_examples: 40
download_size: 38920
dataset_size: 20426
configs:
- config_name: tokenizer_robustness_completion_italian_abbreviations
data_files:
- split: test
path: tokenizer_robustness_completion_italian_abbreviations/test-*
- config_name: tokenizer_robustness_completion_italian_canonical
data_files:
- split: test
path: tokenizer_robustness_completion_italian_canonical/test-*
- config_name: tokenizer_robustness_completion_italian_capitalization
data_files:
- split: test
path: tokenizer_robustness_completion_italian_capitalization/test-*
- config_name: tokenizer_robustness_completion_italian_code_language_script_switching
data_files:
- split: test
path: >-
tokenizer_robustness_completion_italian_code_language_script_switching/test-*
- config_name: tokenizer_robustness_completion_italian_contractions
data_files:
- split: test
path: tokenizer_robustness_completion_italian_contractions/test-*
- config_name: tokenizer_robustness_completion_italian_date_formats
data_files:
- split: test
path: tokenizer_robustness_completion_italian_date_formats/test-*
- config_name: tokenizer_robustness_completion_italian_dialects
data_files:
- split: test
path: tokenizer_robustness_completion_italian_dialects/test-*
- config_name: tokenizer_robustness_completion_italian_english_keyboard
data_files:
- split: test
path: tokenizer_robustness_completion_italian_english_keyboard/test-*
- config_name: tokenizer_robustness_completion_italian_grammatical_errors
data_files:
- split: test
path: tokenizer_robustness_completion_italian_grammatical_errors/test-*
- config_name: tokenizer_robustness_completion_italian_keyboard_proximity_errors
data_files:
- split: test
path: >-
tokenizer_robustness_completion_italian_keyboard_proximity_errors/test-*
- config_name: tokenizer_robustness_completion_italian_numerical_formats
data_files:
- split: test
path: tokenizer_robustness_completion_italian_numerical_formats/test-*
- config_name: tokenizer_robustness_completion_italian_orthographic_errors
data_files:
- split: test
path: tokenizer_robustness_completion_italian_orthographic_errors/test-*
- config_name: tokenizer_robustness_completion_italian_phonetic_spelling
data_files:
- split: test
path: tokenizer_robustness_completion_italian_phonetic_spelling/test-*
- config_name: tokenizer_robustness_completion_italian_plausible_diacritics_errors
data_files:
- split: test
path: >-
tokenizer_robustness_completion_italian_plausible_diacritics_errors/test-*
- config_name: tokenizer_robustness_completion_italian_similar_words
data_files:
- split: test
path: tokenizer_robustness_completion_italian_similar_words/test-*
- config_name: tokenizer_robustness_completion_italian_spelled_out
data_files:
- split: test
path: tokenizer_robustness_completion_italian_spelled_out/test-*
- config_name: tokenizer_robustness_completion_italian_typographical_errors
data_files:
- split: test
path: tokenizer_robustness_completion_italian_typographical_errors/test-*
- config_name: tokenizer_robustness_completion_italian_web_search_query
data_files:
- split: test
path: tokenizer_robustness_completion_italian_web_search_query/test-*
language:
- it
- en
size_categories:
- 1K<n<10K
Dataset Card for Tokenization Robustness
TokSuite Benchmark (Italian Collection)
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 Italian language multiple-choice text completion questions with various real-world perturbations that test tokenizer robustness.
- Curated by: R3 Research Team
- Language(s): Italian (It)
- License: MIT License
Dataset Summary
TokSuite addresses a fundamental challenge in language model research: understanding how tokenization choices impact model behavior in isolation. The Italian 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 Italian
- Parallel structure with TokSuite benchmark (available in English, Turkish, Farsi, Chinese)
- Native speaker curation ensuring linguistic authenticity
Supported Tasks
- 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 Italian text understanding
Languages
The dataset contains text in Italian (language code: ita_Latn / it).
Dataset Structure
Data Fields
| Field | Type | Description |
|---|---|---|
question |
string |
The question text in Italian |
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:
- Systematically evaluate how different tokenization strategies handle Italian
- Measure robustness against real-world text perturbations specific to Italian
- Support research into the impact of tokenization on language model behavior
- Provide standardized benchmarks for Italian language models
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 Italian speakers translated questions
- Perturbations: Each question underwent targeted perturbations designed to reflect Italian characteristics
- Validation: Model-in-the-loop process ensured high baseline accuracy
Perturbation Categories
Canonical The original Italian question written in standard, well-formed Italian with correct spelling, grammar, accents, capitalization, and formatting. All other perturbations are derived from this version and preserve its meaning.
Abbreviations Words or expressions in the canonical sentence are replaced with common Italian abbreviations (e.g., titles like
Dr., shortened forms such asecc.orn.). The semantic content remains unchanged, but surface length and token boundaries are altered.Capitalization Capital letters are altered relative to the canonical form (e.g., sentence-level lowercasing, random capitalization, or improper casing of proper nouns). The lexical content is the same, but casing information is corrupted or inconsistent.
Code / Language / Script Switching Italian sentences contain inserted English words or phrases (often technical terms or borrowed expressions). The script remains Latin, but language identity switches mid-sentence, reflecting realistic bilingual or mixed-language usage.
Contractions Italian elisions and contractions are introduced or modified (e.g.,
l’amico,dell’acqua,all’università). Apostrophes merge words that are separate in canonical form, changing token segmentation while preserving meaning.Date Formats Dates are rewritten using alternative Italian or international formats (e.g., numeric dates, month-name formats, different separators). The temporal meaning is preserved, but punctuation and numeric structure vary.
Dialects Standard Italian words or constructions are replaced with dialect-influenced variants (e.g., regional lexical or morphological forms). These versions remain interpretable to native speakers but diverge from standardized Italian orthography.
English Keyboard Italian text is written as if typed on an English keyboard, resulting in missing or simplified accented characters (e.g.,
percheinstead ofperché). Unicode accents are dropped or normalized, stressing tokenizer handling of diacritics.Grammatical Errors The sentence includes plausible grammatical mistakes such as incorrect agreement, article misuse, or tense errors. The sentence remains understandable, but violates formal Italian grammar rules.
Keyboard Proximity Errors Introduces typos caused by pressing adjacent keys on a keyboard, simulating realistic typing errors without altering intended meaning.
Numerical Formats Numbers are rewritten using different Italian-appropriate formats (e.g., thousand separators, decimal symbols, or spacing). The numeric value is preserved while its surface representation changes.
Orthographic Errors Spelling errors are introduced that violate standard Italian orthography (e.g., incorrect consonant doubling, wrong letter choice). These errors are visually or phonetically plausible but formally incorrect.
Phonetic Spelling Words are spelled according to pronunciation rather than standard orthography, often resembling informal or speech-based writing. This alters character sequences while preserving phonetic identity.
Plausible Diacritics Errors Introduces missing, incorrect, or misplaced diacritics (e.g.,
evs.è,perchévs.perche), testing tokenizer sensitivity to accent marks that affect meaning.Similar Words Canonical words are replaced with closely related or confusable alternatives (e.g., near-synonyms or minimal lexical contrasts). The sentence remains plausible and grammatical but is lexically altered.
Spelled-Out Forms Digits, abbreviations, or compact expressions are replaced with their fully spelled-out Italian equivalents (e.g., numerals written as words). This increases token length and changes lexical composition without changing meaning.
Typographical Errors General typing mistakes are introduced, such as duplicated letters, missing characters, or minor corruptions. These errors are less systematic than keyboard-proximity errors and reflect careless typing.
Web Search Query The question is rewritten in the style of an Italian web search query: function words may be dropped, word order simplified, and phrasing becomes keyword-like rather than sentence-like, while retaining the same informational intent.
Who are the source data producers?
Native Italian 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 Italian text processing.
Who are the annotators?
Native Italian 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 Italian speakers by enabling better understanding of tokenization challenges and supporting more robust multilingual models.
Discussion of Biases
- Language variety:The dataset uses Standard Italian (Italiano standard) and may not fully represent regional or dialectal variations.
- Script focus: Only the Latin script is used; accent and keyboard-related variations are included as perturbations.
- Domain coverage: Questions focus on general knowledge and may not represent domain-specific Italian 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:
@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
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
Contact
For questions or issues related to this dataset, please refer to the TokSuite project or contact the authors of the paper.
Part of the TokSuite Project
Understanding Tokenization's Role in Language Model Behavior