Banning filler words like 'very' and 'just' improved LLM reasoning by 6.7 percentage points while E-Prime improved it by only 3.7, with gains ranking in exact inverse order of theoretical depth across models and tasks.
Chain-of-thought prompting elicits reasoning in large language models.NeurIPS 2022
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Trivial Vocabulary Bans Improve LLM Reasoning More Than Deep Linguistic Constraints
Banning filler words like 'very' and 'just' improved LLM reasoning by 6.7 percentage points while E-Prime improved it by only 3.7, with gains ranking in exact inverse order of theoretical depth across models and tasks.