--- license: mit multilinguality: multilingual task_categories: - multiple-choice pretty_name: Tokenization Robustness tags: - tokenization - robustness dataset_info: - config_name: tokenizer_robustness_completion_stem_canonical features: - name: question dtype: string - name: choices list: string - name: answer dtype: int64 - name: answer_label dtype: string - name: split dtype: string - name: subcategories dtype: string - name: lang dtype: string - name: second_lang dtype: string - name: notes dtype: string - name: id dtype: string - name: set_id dtype: string - name: variation_id dtype: string - name: question_general_category dtype: string - name: vanilla_cos_sim_to_canonical struct: - name: CohereLabs/aya-expanse-8b dtype: float64 - name: Qwen/Qwen3-8B dtype: float64 - name: bigscience/bloom dtype: float64 - name: common-pile/comma-v0.1-1t dtype: float64 - name: facebook/xglm-564M dtype: float64 - name: google-bert/bert-base-multilingual-cased dtype: float64 - name: google/byt5-small dtype: float64 - name: google/gemma-2-2b dtype: float64 - name: gpt2 dtype: float64 - name: meta-llama/Llama-3.2-1B dtype: float64 - name: microsoft/Phi-3-mini-4k-instruct dtype: float64 - name: mistralai/tekken dtype: float64 - name: tiktoken/gpt-4o dtype: float64 - name: tokenmonster/englishcode-32000-consistent-v1 dtype: float64 - name: trimmed_cos_sim_to_canonical struct: - 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: 23517 num_examples: 44 download_size: 32406 dataset_size: 23517 - config_name: tokenizer_robustness_completion_stem_character_deletion features: - name: question dtype: string - name: choices list: string - name: answer dtype: int64 - name: answer_label dtype: string - name: split dtype: string - name: subcategories dtype: string - name: lang dtype: string - name: second_lang dtype: string - name: notes dtype: string - name: id dtype: string - name: set_id dtype: string - name: variation_id dtype: string - name: question_general_category dtype: string - name: vanilla_cos_sim_to_canonical struct: - name: CohereLabs/aya-expanse-8b dtype: float64 - name: Qwen/Qwen3-8B dtype: float64 - name: bigscience/bloom dtype: float64 - name: common-pile/comma-v0.1-1t dtype: float64 - name: facebook/xglm-564M dtype: float64 - name: google-bert/bert-base-multilingual-cased dtype: float64 - name: google/byt5-small dtype: float64 - name: google/gemma-2-2b dtype: float64 - name: gpt2 dtype: float64 - name: meta-llama/Llama-3.2-1B dtype: float64 - name: microsoft/Phi-3-mini-4k-instruct dtype: float64 - name: mistralai/tekken dtype: float64 - name: tiktoken/gpt-4o dtype: float64 - name: tokenmonster/englishcode-32000-consistent-v1 dtype: float64 - name: trimmed_cos_sim_to_canonical struct: - 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: 22723 num_examples: 41 download_size: 40680 dataset_size: 22723 - config_name: tokenizer_robustness_completion_stem_colloquial features: - name: question dtype: string - name: choices list: string - name: answer dtype: int64 - name: answer_label dtype: string - name: split dtype: string - name: subcategories dtype: string - name: lang dtype: string - name: second_lang dtype: string - name: notes dtype: string - name: id dtype: string - name: set_id dtype: string - name: variation_id dtype: string - name: question_general_category dtype: string - name: vanilla_cos_sim_to_canonical struct: - name: CohereLabs/aya-expanse-8b dtype: float64 - name: Qwen/Qwen3-8B dtype: float64 - name: bigscience/bloom dtype: float64 - name: common-pile/comma-v0.1-1t dtype: float64 - name: facebook/xglm-564M dtype: float64 - name: google-bert/bert-base-multilingual-cased dtype: float64 - name: google/byt5-small dtype: float64 - name: google/gemma-2-2b dtype: float64 - name: gpt2 dtype: float64 - name: meta-llama/Llama-3.2-1B dtype: float64 - name: microsoft/Phi-3-mini-4k-instruct dtype: float64 - name: mistralai/tekken dtype: float64 - name: tiktoken/gpt-4o dtype: float64 - name: tokenmonster/englishcode-32000-consistent-v1 dtype: float64 - name: trimmed_cos_sim_to_canonical struct: - 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: 7820 num_examples: 15 download_size: 32313 dataset_size: 7820 - config_name: tokenizer_robustness_completion_stem_compounds features: - name: question dtype: string - name: choices list: string - name: answer dtype: int64 - name: answer_label dtype: string - name: split dtype: string - name: subcategories dtype: string - name: lang dtype: string - name: second_lang dtype: string - name: notes dtype: string - name: id dtype: string - name: set_id dtype: string - name: variation_id dtype: string - name: question_general_category dtype: string - name: vanilla_cos_sim_to_canonical struct: - name: CohereLabs/aya-expanse-8b dtype: float64 - name: Qwen/Qwen3-8B dtype: float64 - name: bigscience/bloom dtype: float64 - name: common-pile/comma-v0.1-1t dtype: float64 - name: facebook/xglm-564M dtype: float64 - name: google-bert/bert-base-multilingual-cased dtype: float64 - name: google/byt5-small dtype: float64 - name: google/gemma-2-2b dtype: float64 - name: gpt2 dtype: float64 - name: meta-llama/Llama-3.2-1B dtype: float64 - name: microsoft/Phi-3-mini-4k-instruct dtype: float64 - name: mistralai/tekken dtype: float64 - name: tiktoken/gpt-4o dtype: float64 - name: tokenmonster/englishcode-32000-consistent-v1 dtype: float64 - name: trimmed_cos_sim_to_canonical struct: - 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: 566 num_examples: 1 download_size: 27881 dataset_size: 566 - config_name: tokenizer_robustness_completion_stem_diacriticized_styling features: - name: question dtype: string - name: choices list: string - name: answer dtype: int64 - name: answer_label dtype: string - name: split dtype: string - name: subcategories dtype: string - name: lang dtype: string - name: second_lang dtype: string - name: notes dtype: string - name: id dtype: string - name: set_id dtype: string - name: variation_id dtype: string - name: question_general_category dtype: string - name: vanilla_cos_sim_to_canonical struct: - name: CohereLabs/aya-expanse-8b dtype: float64 - name: Qwen/Qwen3-8B dtype: float64 - name: bigscience/bloom dtype: float64 - name: common-pile/comma-v0.1-1t dtype: float64 - name: facebook/xglm-564M dtype: float64 - name: google-bert/bert-base-multilingual-cased dtype: float64 - name: google/byt5-small dtype: float64 - name: google/gemma-2-2b dtype: float64 - name: gpt2 dtype: float64 - name: meta-llama/Llama-3.2-1B dtype: float64 - name: microsoft/Phi-3-mini-4k-instruct dtype: float64 - name: mistralai/tekken dtype: float64 - name: tiktoken/gpt-4o dtype: float64 - name: tokenmonster/englishcode-32000-consistent-v1 dtype: float64 - name: trimmed_cos_sim_to_canonical struct: - 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: 32623 num_examples: 55 download_size: 33837 dataset_size: 32623 - config_name: tokenizer_robustness_completion_stem_double_struck features: - name: question dtype: string - name: choices list: string - name: answer dtype: int64 - name: answer_label dtype: string - name: split dtype: string - name: subcategories dtype: string - name: lang dtype: string - name: second_lang dtype: string - name: notes dtype: string - name: id dtype: string - name: set_id dtype: string - name: variation_id dtype: string - name: question_general_category dtype: string - name: vanilla_cos_sim_to_canonical struct: - name: CohereLabs/aya-expanse-8b dtype: float64 - name: Qwen/Qwen3-8B dtype: float64 - name: bigscience/bloom dtype: float64 - name: common-pile/comma-v0.1-1t dtype: float64 - name: facebook/xglm-564M dtype: float64 - name: google-bert/bert-base-multilingual-cased dtype: float64 - name: google/byt5-small dtype: float64 - name: google/gemma-2-2b dtype: float64 - name: gpt2 dtype: float64 - name: meta-llama/Llama-3.2-1B dtype: float64 - name: microsoft/Phi-3-mini-4k-instruct dtype: float64 - name: mistralai/tekken dtype: float64 - name: tiktoken/gpt-4o dtype: float64 - name: tokenmonster/englishcode-32000-consistent-v1 dtype: float64 - name: trimmed_cos_sim_to_canonical struct: - 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: 11237 num_examples: 18 download_size: 31336 dataset_size: 11237 - config_name: tokenizer_robustness_completion_stem_enclosed_characters features: - name: question dtype: string - name: choices list: string - name: answer dtype: int64 - name: answer_label dtype: string - name: split dtype: string - name: subcategories dtype: string - name: lang dtype: string - name: second_lang dtype: string - name: notes dtype: string - name: id dtype: string - name: set_id dtype: string - name: variation_id dtype: string - name: question_general_category dtype: string - name: vanilla_cos_sim_to_canonical struct: - name: CohereLabs/aya-expanse-8b dtype: float64 - name: Qwen/Qwen3-8B dtype: float64 - name: bigscience/bloom dtype: float64 - name: common-pile/comma-v0.1-1t dtype: float64 - name: facebook/xglm-564M dtype: float64 - name: google-bert/bert-base-multilingual-cased dtype: float64 - name: google/byt5-small dtype: float64 - name: google/gemma-2-2b dtype: float64 - name: gpt2 dtype: float64 - name: meta-llama/Llama-3.2-1B dtype: float64 - name: microsoft/Phi-3-mini-4k-instruct dtype: float64 - name: mistralai/tekken dtype: float64 - name: tiktoken/gpt-4o dtype: float64 - name: tokenmonster/englishcode-32000-consistent-v1 dtype: float64 - name: trimmed_cos_sim_to_canonical struct: - 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: 25460 num_examples: 42 download_size: 32767 dataset_size: 25460 - config_name: tokenizer_robustness_completion_stem_equivalent_expressions features: - name: question dtype: string - name: choices list: string - name: answer dtype: int64 - name: answer_label dtype: string - name: split dtype: string - name: subcategories dtype: string - name: lang dtype: string - name: second_lang dtype: string - name: notes dtype: string - name: id dtype: string - name: set_id dtype: string - name: variation_id dtype: string - name: question_general_category dtype: string - name: vanilla_cos_sim_to_canonical struct: - name: CohereLabs/aya-expanse-8b dtype: float64 - name: Qwen/Qwen3-8B dtype: float64 - name: bigscience/bloom dtype: float64 - name: common-pile/comma-v0.1-1t dtype: float64 - name: facebook/xglm-564M dtype: float64 - name: google-bert/bert-base-multilingual-cased dtype: float64 - name: google/byt5-small dtype: float64 - name: google/gemma-2-2b dtype: float64 - name: gpt2 dtype: float64 - name: meta-llama/Llama-3.2-1B dtype: float64 - name: microsoft/Phi-3-mini-4k-instruct dtype: float64 - name: mistralai/tekken dtype: float64 - name: tiktoken/gpt-4o dtype: float64 - name: tokenmonster/englishcode-32000-consistent-v1 dtype: float64 - name: trimmed_cos_sim_to_canonical struct: - 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: 8286 num_examples: 15 download_size: 32741 dataset_size: 8286 - config_name: tokenizer_robustness_completion_stem_fullwidth_characters features: - name: question dtype: string - name: choices list: string - name: answer dtype: int64 - name: answer_label dtype: string - name: split dtype: string - name: subcategories dtype: string - name: lang dtype: string - name: second_lang dtype: string - name: notes dtype: string - name: id dtype: string - name: set_id dtype: string - name: variation_id dtype: string - name: question_general_category dtype: string - name: vanilla_cos_sim_to_canonical struct: - name: CohereLabs/aya-expanse-8b dtype: float64 - name: Qwen/Qwen3-8B dtype: float64 - name: bigscience/bloom dtype: float64 - name: common-pile/comma-v0.1-1t dtype: float64 - name: facebook/xglm-564M dtype: float64 - name: google-bert/bert-base-multilingual-cased dtype: float64 - name: google/byt5-small dtype: float64 - name: google/gemma-2-2b dtype: float64 - name: gpt2 dtype: float64 - name: meta-llama/Llama-3.2-1B dtype: float64 - name: microsoft/Phi-3-mini-4k-instruct dtype: float64 - name: mistralai/tekken dtype: float64 - name: tiktoken/gpt-4o dtype: float64 - name: tokenmonster/englishcode-32000-consistent-v1 dtype: float64 - name: trimmed_cos_sim_to_canonical struct: - 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: 10163 num_examples: 17 download_size: 31032 dataset_size: 10163 - config_name: tokenizer_robustness_completion_stem_latex features: - name: question dtype: string - name: choices list: string - name: answer dtype: int64 - name: answer_label dtype: string - name: split dtype: string - name: subcategories dtype: string - name: lang dtype: string - name: second_lang dtype: string - name: notes dtype: string - name: id dtype: string - name: set_id dtype: string - name: variation_id dtype: string - name: question_general_category dtype: string - name: vanilla_cos_sim_to_canonical struct: - name: CohereLabs/aya-expanse-8b dtype: float64 - name: Qwen/Qwen3-8B dtype: float64 - name: bigscience/bloom dtype: float64 - name: common-pile/comma-v0.1-1t dtype: float64 - name: facebook/xglm-564M dtype: float64 - name: google-bert/bert-base-multilingual-cased dtype: float64 - name: google/byt5-small dtype: float64 - name: google/gemma-2-2b dtype: float64 - name: gpt2 dtype: float64 - name: meta-llama/Llama-3.2-1B dtype: float64 - name: microsoft/Phi-3-mini-4k-instruct dtype: float64 - name: mistralai/tekken dtype: float64 - name: tiktoken/gpt-4o dtype: float64 - name: tokenmonster/englishcode-32000-consistent-v1 dtype: float64 - name: trimmed_cos_sim_to_canonical struct: - 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: 35181 num_examples: 68 download_size: 44974 dataset_size: 35181 - config_name: tokenizer_robustness_completion_stem_morpheme_separation features: - name: question dtype: string - name: choices list: string - name: answer dtype: int64 - name: answer_label dtype: string - name: split dtype: string - name: subcategories dtype: string - name: lang dtype: string - name: second_lang dtype: string - name: notes dtype: string - name: id dtype: string - name: set_id dtype: string - name: variation_id dtype: string - name: question_general_category dtype: string - name: vanilla_cos_sim_to_canonical struct: - name: CohereLabs/aya-expanse-8b dtype: float64 - name: Qwen/Qwen3-8B dtype: float64 - name: bigscience/bloom dtype: float64 - name: common-pile/comma-v0.1-1t dtype: float64 - name: facebook/xglm-564M dtype: float64 - name: google-bert/bert-base-multilingual-cased dtype: float64 - name: google/byt5-small dtype: float64 - name: google/gemma-2-2b dtype: float64 - name: gpt2 dtype: float64 - name: meta-llama/Llama-3.2-1B dtype: float64 - name: microsoft/Phi-3-mini-4k-instruct dtype: float64 - name: mistralai/tekken dtype: float64 - name: tiktoken/gpt-4o dtype: float64 - name: tokenmonster/englishcode-32000-consistent-v1 dtype: float64 - name: trimmed_cos_sim_to_canonical struct: - 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: 18619 num_examples: 34 download_size: 38084 dataset_size: 18619 - config_name: tokenizer_robustness_completion_stem_scripted_text features: - name: question dtype: string - name: choices list: string - name: answer dtype: int64 - name: answer_label dtype: string - name: split dtype: string - name: subcategories dtype: string - name: lang dtype: string - name: second_lang dtype: string - name: notes dtype: string - name: id dtype: string - name: set_id dtype: string - name: variation_id dtype: string - name: question_general_category dtype: string - name: vanilla_cos_sim_to_canonical struct: - name: CohereLabs/aya-expanse-8b dtype: float64 - name: Qwen/Qwen3-8B dtype: float64 - name: bigscience/bloom dtype: float64 - name: common-pile/comma-v0.1-1t dtype: float64 - name: facebook/xglm-564M dtype: float64 - name: google-bert/bert-base-multilingual-cased dtype: float64 - name: google/byt5-small dtype: float64 - name: google/gemma-2-2b dtype: float64 - name: gpt2 dtype: float64 - name: meta-llama/Llama-3.2-1B dtype: float64 - name: microsoft/Phi-3-mini-4k-instruct dtype: float64 - name: mistralai/tekken dtype: float64 - name: tiktoken/gpt-4o dtype: float64 - name: tokenmonster/englishcode-32000-consistent-v1 dtype: float64 - name: trimmed_cos_sim_to_canonical struct: - 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: 11267 num_examples: 18 download_size: 31156 dataset_size: 11267 - config_name: tokenizer_robustness_completion_stem_space_removal features: - name: question dtype: string - name: choices list: string - name: answer dtype: int64 - name: answer_label dtype: string - name: split dtype: string - name: subcategories dtype: string - name: lang dtype: string - name: second_lang dtype: string - name: notes dtype: string - name: id dtype: string - name: set_id dtype: string - name: variation_id dtype: string - name: question_general_category dtype: string - name: vanilla_cos_sim_to_canonical struct: - name: CohereLabs/aya-expanse-8b dtype: float64 - name: Qwen/Qwen3-8B dtype: float64 - name: bigscience/bloom dtype: float64 - name: common-pile/comma-v0.1-1t dtype: float64 - name: facebook/xglm-564M dtype: float64 - name: google-bert/bert-base-multilingual-cased dtype: float64 - name: google/byt5-small dtype: float64 - name: google/gemma-2-2b dtype: float64 - name: gpt2 dtype: float64 - name: meta-llama/Llama-3.2-1B dtype: float64 - name: microsoft/Phi-3-mini-4k-instruct dtype: float64 - name: mistralai/tekken dtype: float64 - name: tiktoken/gpt-4o dtype: float64 - name: tokenmonster/englishcode-32000-consistent-v1 dtype: float64 - name: trimmed_cos_sim_to_canonical struct: - 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: 22025 num_examples: 41 download_size: 40316 dataset_size: 22025 - config_name: tokenizer_robustness_completion_stem_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: lang dtype: string - name: second_lang dtype: string - name: notes dtype: string - name: id dtype: string - name: set_id dtype: string - name: variation_id dtype: string - name: question_general_category dtype: string - name: vanilla_cos_sim_to_canonical struct: - name: CohereLabs/aya-expanse-8b dtype: float64 - name: Qwen/Qwen3-8B dtype: float64 - name: bigscience/bloom dtype: float64 - name: common-pile/comma-v0.1-1t dtype: float64 - name: facebook/xglm-564M dtype: float64 - name: google-bert/bert-base-multilingual-cased dtype: float64 - name: google/byt5-small dtype: float64 - name: google/gemma-2-2b dtype: float64 - name: gpt2 dtype: float64 - name: meta-llama/Llama-3.2-1B dtype: float64 - name: microsoft/Phi-3-mini-4k-instruct dtype: float64 - name: mistralai/tekken dtype: float64 - name: tiktoken/gpt-4o dtype: float64 - name: tokenmonster/englishcode-32000-consistent-v1 dtype: float64 - name: trimmed_cos_sim_to_canonical struct: - 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: 13749 num_examples: 25 download_size: 35840 dataset_size: 13749 - config_name: tokenizer_robustness_completion_stem_strikethrough features: - name: question dtype: string - name: choices list: string - name: answer dtype: int64 - name: answer_label dtype: string - name: split dtype: string - name: subcategories dtype: string - name: lang dtype: string - name: second_lang dtype: string - name: notes dtype: string - name: id dtype: string - name: set_id dtype: string - name: variation_id dtype: string - name: question_general_category dtype: string - name: vanilla_cos_sim_to_canonical struct: - name: CohereLabs/aya-expanse-8b dtype: float64 - name: Qwen/Qwen3-8B dtype: float64 - name: bigscience/bloom dtype: float64 - name: common-pile/comma-v0.1-1t dtype: float64 - name: facebook/xglm-564M dtype: float64 - name: google-bert/bert-base-multilingual-cased dtype: float64 - name: google/byt5-small dtype: float64 - name: google/gemma-2-2b dtype: float64 - name: gpt2 dtype: float64 - name: meta-llama/Llama-3.2-1B dtype: float64 - name: microsoft/Phi-3-mini-4k-instruct dtype: float64 - name: mistralai/tekken dtype: float64 - name: tiktoken/gpt-4o dtype: float64 - name: tokenmonster/englishcode-32000-consistent-v1 dtype: float64 - name: trimmed_cos_sim_to_canonical struct: - 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: 31149 num_examples: 52 download_size: 33762 dataset_size: 31149 - config_name: tokenizer_robustness_completion_stem_superscript_subscript features: - name: question dtype: string - name: choices list: string - name: answer dtype: int64 - name: answer_label dtype: string - name: split dtype: string - name: subcategories dtype: string - name: lang dtype: string - name: second_lang dtype: string - name: notes dtype: string - name: id dtype: string - name: set_id dtype: string - name: variation_id dtype: string - name: question_general_category dtype: string - name: vanilla_cos_sim_to_canonical struct: - name: CohereLabs/aya-expanse-8b dtype: float64 - name: Qwen/Qwen3-8B dtype: float64 - name: bigscience/bloom dtype: float64 - name: common-pile/comma-v0.1-1t dtype: float64 - name: facebook/xglm-564M dtype: float64 - name: google-bert/bert-base-multilingual-cased dtype: float64 - name: google/byt5-small dtype: float64 - name: google/gemma-2-2b dtype: float64 - name: gpt2 dtype: float64 - name: meta-llama/Llama-3.2-1B dtype: float64 - name: microsoft/Phi-3-mini-4k-instruct dtype: float64 - name: mistralai/tekken dtype: float64 - name: tiktoken/gpt-4o dtype: float64 - name: tokenmonster/englishcode-32000-consistent-v1 dtype: float64 - name: trimmed_cos_sim_to_canonical struct: - 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: 17203 num_examples: 29 download_size: 32747 dataset_size: 17203 - config_name: tokenizer_robustness_completion_stem_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: lang dtype: string - name: second_lang dtype: string - name: notes dtype: string - name: id dtype: string - name: set_id dtype: string - name: variation_id dtype: string - name: question_general_category dtype: string - name: vanilla_cos_sim_to_canonical struct: - name: CohereLabs/aya-expanse-8b dtype: float64 - name: Qwen/Qwen3-8B dtype: float64 - name: bigscience/bloom dtype: float64 - name: common-pile/comma-v0.1-1t dtype: float64 - name: facebook/xglm-564M dtype: float64 - name: google-bert/bert-base-multilingual-cased dtype: float64 - name: google/byt5-small dtype: float64 - name: google/gemma-2-2b dtype: float64 - name: gpt2 dtype: float64 - name: meta-llama/Llama-3.2-1B dtype: float64 - name: microsoft/Phi-3-mini-4k-instruct dtype: float64 - name: mistralai/tekken dtype: float64 - name: tiktoken/gpt-4o dtype: float64 - name: tokenmonster/englishcode-32000-consistent-v1 dtype: float64 - name: trimmed_cos_sim_to_canonical struct: - 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: 21308 num_examples: 38 download_size: 39429 dataset_size: 21308 - config_name: tokenizer_robustness_completion_stem_unicode_formatting features: - name: question dtype: string - name: choices list: string - name: answer dtype: int64 - name: answer_label dtype: string - name: split dtype: string - name: subcategories dtype: string - name: lang dtype: string - name: second_lang dtype: string - name: notes dtype: string - name: id dtype: string - name: set_id dtype: string - name: variation_id dtype: string - name: question_general_category dtype: string - name: vanilla_cos_sim_to_canonical struct: - name: CohereLabs/aya-expanse-8b dtype: float64 - name: Qwen/Qwen3-8B dtype: float64 - name: bigscience/bloom dtype: float64 - name: common-pile/comma-v0.1-1t dtype: float64 - name: facebook/xglm-564M dtype: float64 - name: google-bert/bert-base-multilingual-cased dtype: float64 - name: google/byt5-small dtype: float64 - name: google/gemma-2-2b dtype: float64 - name: gpt2 dtype: float64 - name: meta-llama/Llama-3.2-1B dtype: float64 - name: microsoft/Phi-3-mini-4k-instruct dtype: float64 - name: mistralai/tekken dtype: float64 - name: tiktoken/gpt-4o dtype: float64 - name: tokenmonster/englishcode-32000-consistent-v1 dtype: float64 - name: trimmed_cos_sim_to_canonical struct: - 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: 15211 num_examples: 28 download_size: 35076 dataset_size: 15211 - config_name: tokenizer_robustness_completion_stem_unusual_formatting features: - name: question dtype: string - name: choices list: string - name: answer dtype: int64 - name: answer_label dtype: string - name: split dtype: string - name: subcategories dtype: string - name: lang dtype: string - name: second_lang dtype: string - name: notes dtype: string - name: id dtype: string - name: set_id dtype: string - name: variation_id dtype: string - name: question_general_category dtype: string - name: vanilla_cos_sim_to_canonical struct: - name: CohereLabs/aya-expanse-8b dtype: float64 - name: Qwen/Qwen3-8B dtype: float64 - name: bigscience/bloom dtype: float64 - name: common-pile/comma-v0.1-1t dtype: float64 - name: facebook/xglm-564M dtype: float64 - name: google-bert/bert-base-multilingual-cased dtype: float64 - name: google/byt5-small dtype: float64 - name: google/gemma-2-2b dtype: float64 - name: gpt2 dtype: float64 - name: meta-llama/Llama-3.2-1B dtype: float64 - name: microsoft/Phi-3-mini-4k-instruct dtype: float64 - name: mistralai/tekken dtype: float64 - name: tiktoken/gpt-4o dtype: float64 - name: tokenmonster/englishcode-32000-consistent-v1 dtype: float64 - name: trimmed_cos_sim_to_canonical struct: - 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: 8738 num_examples: 16 download_size: 33085 dataset_size: 8738 - config_name: tokenizer_robustness_completion_stem_upside_down_rotated features: - name: question dtype: string - name: choices list: string - name: answer dtype: int64 - name: answer_label dtype: string - name: split dtype: string - name: subcategories dtype: string - name: lang dtype: string - name: second_lang dtype: string - name: notes dtype: string - name: id dtype: string - name: set_id dtype: string - name: variation_id dtype: string - name: question_general_category dtype: string - name: vanilla_cos_sim_to_canonical struct: - name: CohereLabs/aya-expanse-8b dtype: float64 - name: Qwen/Qwen3-8B dtype: float64 - name: bigscience/bloom dtype: float64 - name: common-pile/comma-v0.1-1t dtype: float64 - name: facebook/xglm-564M dtype: float64 - name: google-bert/bert-base-multilingual-cased dtype: float64 - name: google/byt5-small dtype: float64 - name: google/gemma-2-2b dtype: float64 - name: gpt2 dtype: float64 - name: meta-llama/Llama-3.2-1B dtype: float64 - name: microsoft/Phi-3-mini-4k-instruct dtype: float64 - name: mistralai/tekken dtype: float64 - name: tiktoken/gpt-4o dtype: float64 - name: tokenmonster/englishcode-32000-consistent-v1 dtype: float64 - name: trimmed_cos_sim_to_canonical struct: - 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: 9543 num_examples: 17 download_size: 30880 dataset_size: 9543 configs: - config_name: tokenizer_robustness_completion_stem_canonical data_files: - split: test path: tokenizer_robustness_completion_stem_canonical/test-* - config_name: tokenizer_robustness_completion_stem_character_deletion data_files: - split: test path: tokenizer_robustness_completion_stem_character_deletion/test-* - config_name: tokenizer_robustness_completion_stem_colloquial data_files: - split: test path: tokenizer_robustness_completion_stem_colloquial/test-* - config_name: tokenizer_robustness_completion_stem_compounds data_files: - split: test path: tokenizer_robustness_completion_stem_compounds/test-* - config_name: tokenizer_robustness_completion_stem_diacriticized_styling data_files: - split: test path: tokenizer_robustness_completion_stem_diacriticized_styling/test-* - config_name: tokenizer_robustness_completion_stem_double_struck data_files: - split: test path: tokenizer_robustness_completion_stem_double_struck/test-* - config_name: tokenizer_robustness_completion_stem_enclosed_characters data_files: - split: test path: tokenizer_robustness_completion_stem_enclosed_characters/test-* - config_name: tokenizer_robustness_completion_stem_equivalent_expressions data_files: - split: test path: tokenizer_robustness_completion_stem_equivalent_expressions/test-* - config_name: tokenizer_robustness_completion_stem_fullwidth_characters data_files: - split: test path: tokenizer_robustness_completion_stem_fullwidth_characters/test-* - config_name: tokenizer_robustness_completion_stem_latex data_files: - split: test path: tokenizer_robustness_completion_stem_latex/test-* - config_name: tokenizer_robustness_completion_stem_morpheme_separation data_files: - split: test path: tokenizer_robustness_completion_stem_morpheme_separation/test-* - config_name: tokenizer_robustness_completion_stem_scripted_text data_files: - split: test path: tokenizer_robustness_completion_stem_scripted_text/test-* - config_name: tokenizer_robustness_completion_stem_space_removal data_files: - split: test path: tokenizer_robustness_completion_stem_space_removal/test-* - config_name: tokenizer_robustness_completion_stem_spelled_out data_files: - split: test path: tokenizer_robustness_completion_stem_spelled_out/test-* - config_name: tokenizer_robustness_completion_stem_strikethrough data_files: - split: test path: tokenizer_robustness_completion_stem_strikethrough/test-* - config_name: tokenizer_robustness_completion_stem_superscript_subscript data_files: - split: test path: tokenizer_robustness_completion_stem_superscript_subscript/test-* - config_name: tokenizer_robustness_completion_stem_typographical_errors data_files: - split: test path: tokenizer_robustness_completion_stem_typographical_errors/test-* - config_name: tokenizer_robustness_completion_stem_unicode_formatting data_files: - split: test path: tokenizer_robustness_completion_stem_unicode_formatting/test-* - config_name: tokenizer_robustness_completion_stem_unusual_formatting data_files: - split: test path: tokenizer_robustness_completion_stem_unusual_formatting/test-* - config_name: tokenizer_robustness_completion_stem_upside_down_rotated data_files: - split: test path: tokenizer_robustness_completion_stem_upside_down_rotated/test-* language: - en size_categories: - n<1K --- # Dataset Card for Tokenization Robustness TokSuite Logo # TokSuite Benchmark (STEM Collection) ## Dataset Description This dataset is the **STEM subset** of the **TokSuite** benchmark, designed to evaluate how tokenizer choice affects model behavior under **realistic formatting, notation, and surface-form perturbations** in technical text. TokSuite includes specialized benchmarks for **mathematics and STEM**, with the STEM subset containing **44 canonical technical questions** paired with a diverse set of targeted perturbations. - **Curated by:** R3 Research Team - **License:** MIT License ### Dataset Summary TokSuite addresses a fundamental challenge in language model research: understanding how **tokenization choices impact model behavior in isolation**, independent of architecture, training data, or optimization. The **STEM subset** specifically measures model performance on **technical and scientific questions** under perturbations that commonly arise in real-world STEM communication, including **Unicode formatting, mathematical notation, LaTeX representations, spacing changes, and visual styling variants**. **Key Features:** - 44 canonical STEM questions covering science, mathematics, engineering, and technical reasoning - A wide range of formatting- and notation-based perturbations reflecting real-world technical text - Parallel structure with other TokSuite benchmark subsets - Designed for controlled robustness evaluation with high baseline accuracy ### Supported Tasks - **Multiple-Choice Question Answering**: Text completion format with 4 answer choices - **Tokenizer Robustness Evaluation**: Measuring performance degradation under surface-form and formatting perturbations - **Technical Text Understanding**: Evaluating model robustness on STEM-style content ### Languages The dataset is primarily in **English** (`en`), with variations expressed through **symbolic, typographic, and Unicode transformations** rather than natural-language translation. --- ## Dataset Structure ### Data Fields | Field | Type | Description | |------|------|-------------| | `question` | `string` | The STEM question text | | `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 (`en`) | | `second_lang` | `string` | Optional plain-text or alternative representation | | `notes` | `string` | Additional context about the 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 to canonical form (raw tokens) | | `trimmed_cos_sim_to_canonical` | `dict[string, float]` | Cosine similarity after token normalization | | `token_counts` | `dict[string, integer]` | Token counts per tokenizer | --- ## Dataset Creation ### Curation Rationale This dataset was created to: 1. Systematically evaluate how different tokenization strategies handle **STEM-style text** 2. Measure robustness to **formatting, notation, and Unicode-based perturbations** 3. Isolate tokenizer effects from semantic reasoning difficulty 4. Provide standardized benchmarks for technical text robustness analysis The questions were intentionally designed to be **conceptually straightforward**, ensuring high canonical accuracy and enabling clean measurement of performance degradation due solely to perturbations. ### Source Data #### Data Collection and Processing - **Canonical Questions**: 44 STEM questions authored in clean, standard technical English - **Perturbations**: Each question was transformed using targeted surface-form and formatting variations - **Validation**: Model-in-the-loop filtering ensured canonical questions are answerable with high accuracy --- ## Perturbation Categories Each perturbation preserves the **underlying semantic intent** of the canonical STEM question while modifying its **surface form, notation, or formatting** to stress tokenizer behavior. All perturbations are paired with the same canonical question and differ only in representation. ### 1. Canonical Clean, standard technical English with conventional notation, spacing, and formatting. This serves as the reference condition for evaluating robustness. ### 2. Character Deletion Removes one or more characters from technical terms, symbols, or variables (e.g., `markup → markp`). These deletions are subtle but often catastrophic for subword tokenization, especially in STEM terminology. ### 3. Colloquial Rewrites the question using more informal or descriptive language while preserving technical meaning. This tests robustness to register changes without altering core content. ### 4. Compounds Alters compound technical terms by merging or restructuring components (e.g., removing separators or introducing fused forms), changing token boundaries and segmentation behavior. ### 5. Diacriticized Styling Introduces decorative or combining diacritics applied to characters in technical text. These perturbations preserve visual similarity but change Unicode code points and normalization behavior. ### 6. Double-Struck Characters Replaces standard Latin characters with mathematical double-struck Unicode forms (e.g., `R → ℝ`, `Z → ℤ`), commonly used in mathematical notation. ### 7. Enclosed Characters Substitutes alphanumeric characters with enclosed Unicode variants (e.g., `A → Ⓐ`, `1 → ①`), which are visually similar but tokenized very differently. ### 8. Equivalent Expressions Rewrites the same STEM concept using an alternative but semantically equivalent formulation, such as paraphrasing definitions or reordering explanatory clauses. ### 9. Fullwidth Characters Uses fullwidth Unicode forms (e.g., `A → A`, `1 → 1`) instead of standard ASCII characters, altering byte-level and subword tokenization. ### 10. LaTeX Represents mathematical expressions or symbols using LaTeX-style notation (e.g., `$x^2$`, `$N_2$`, `\frac{a}{b}`), reflecting common technical writing practices. ### 11. Morpheme Separation Artificially splits technical terms into smaller morpheme-like units, increasing sequence length and disrupting learned subword patterns. ### 12. Scripted Text Uses scripted or calligraphic Unicode variants of characters (e.g., `𝒜𝒷𝒸`) in place of standard Latin letters, stressing visual–semantic mismatch handling. ### 13. Space Removal Removes or alters whitespace that is normally meaningful in technical text, such as between variables, units, or multi-word terms. ### 14. Spelled-Out Replaces numerals, symbols, or abbreviated technical forms with fully spelled-out textual equivalents (e.g., `2 → two`, `H2O → water molecule`). ### 15. Strikethrough Applies strikethrough, combining characters or formatting marks to portions of text, preserving content but introducing visual and Unicode noise. ### 16. Superscript / Subscript Uses Unicode superscript and subscript characters (e.g., `x²`, `N₂`) instead of linear text representations, which often fragment tokenization. ### 17. Typographical Errors Introduces realistic typos such as missing letters, duplicated characters, or minor corruptions common in fast technical writing. ### 18. Unicode Formatting Applies Unicode formatting characters that affect text rendering or directionality while leaving the visible content largely unchanged. ### 19. Unusual Formatting Introduces nonstandard layout, punctuation, or visual formatting patterns that are uncommon but realistic in technical documents. ### 20. Upside-Down / Rotated Uses visually rotated or upside-down Unicode characters that resemble standard characters but differ at the code-point level. --- ## Considerations for Using the Data ### Social Impact of Dataset This dataset supports the development of **more robust language models for technical and scientific domains**, improving reliability in education, research, and engineering applications. ### Discussion of Biases - **Domain focus**: Emphasizes STEM-style technical text rather than natural language discourse - **Formatting-centric**: Perturbations focus on surface form, not conceptual difficulty - **English-centric**: Uses English technical text, though many perturbations are language-agnostic - **Question simplicity**: Designed for robustness evaluation rather than deep problem-solving ### Other Known Limitations - Evaluation-only dataset (no training split) - Multiple-choice format - Limited question count per perturbation - Results may differ for long-form or open-ended STEM reasoning --- ## 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](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*