Chain-of-Thought Prompting Elicits Reasoning in Large Language Models
Early research on using worked reasoning examples to improve performance on reasoning tasks.
The paper studies how worked reasoning examples affect language-model performance on reasoning tasks. It offers historical context for later approaches without guaranteeing reliable reasoning in every model.
- Level
- Advanced
- Models
- any
- Category
- Prompting
- Tags
- reasoning, research
- Source date
- 2022-01-28
- Added
- 2026-10-18
- Last verified
- 2026-10-18
- Status
- ok
- Prerequisites
- Requires implementation experience or critical reading of technical methods and system trade-offs.
- Subcategory
- reasoning and structured output
- Region
- West
- Original language
- en
- Access
- free
- Resource reuse
- open: Source states by/4.0. Applies to the linked resource, not every referenced model or dataset. Facet definitions
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