--- 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 TokSuite Logo # 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: 1. Systematically evaluate how different tokenization strategies handle Italian 2. Measure robustness against real-world text perturbations specific to Italian 3. Support research into the impact of tokenization on language model behavior 4. 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 1. **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. 2. **Abbreviations** Words or expressions in the canonical sentence are replaced with common Italian abbreviations (e.g., titles like `Dr.`, shortened forms such as `ecc.` or `n.`). The semantic content remains unchanged, but surface length and token boundaries are altered. 3. **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. 4. **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. 5. **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. 6. **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. 7. **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. 8. **English Keyboard** Italian text is written as if typed on an English keyboard, resulting in missing or simplified accented characters (e.g., `perche` instead of `perché`). Unicode accents are dropped or normalized, stressing tokenizer handling of diacritics. 9. **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. 10. **Keyboard Proximity Errors** Introduces typos caused by pressing adjacent keys on a keyboard, simulating realistic typing errors without altering intended meaning. 11. **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. 12. **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. 12. **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. 14. **Plausible Diacritics Errors** Introduces missing, incorrect, or misplaced diacritics (e.g., `e` vs. `è`, `perché` vs. `perche`), testing tokenizer sensitivity to accent marks that affect meaning. 15. **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. 16. **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. 17. **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. 18. **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: ```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 - 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](TBD)** *Understanding Tokenization's Role in Language Model Behavior*