The Art of SOCRATIC QUESTIONING: Recursive Thinking with Large Language Models Article Swipe
Jingyuan Qi
,
Zhiyang Xu
,
Ying Shen
,
Min‐Qian Liu
,
Di Jin
,
Qifan Wang
,
Lifu Huang
·
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.18653/v1/2023.emnlp-main.255
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.18653/v1/2023.emnlp-main.255
Chain-of-Thought (CoT) prompting enables large language models to solve complex reasoning problems by generating intermediate steps. However, confined by its inherent single-pass and sequential generation process, CoT heavily relies on the initial decisions, causing errors in early steps to accumulate and impact the final answers. In contrast, humans adopt recursive thinking when tackling complex reasoning problems, i.e. iteratively breaking the original problem into approachable sub-problems and aggregating their answers to resolve the original one. Inspired by the human cognitive process, we propose SOCRATIC QUESTIONING, a divide-and-conquer style algorithm that mimics the recursive thinking process. Specifically, SOCRATIC QUESTIONING leverages large language models to raise and answer sub-questions until collecting enough information to tackle the original question. Unlike CoT, SOCRATIC QUESTIONING explicitly navigates the thinking space, stimulates effective recursive thinking, and is more robust towards errors in the thinking process. Extensive experiments on several complex reasoning tasks, including MMLU, MATH, LogiQA, and visual question-answering demonstrate significant performance improvements over the state-of-the-art prompting methods, such as CoT, and Tree-of-Thought. The qualitative analysis clearly shows that the intermediate reasoning steps elicited by SOCRATIC QUESTIONING are similar to humans’ recursively thinking process of complex reasoning problems.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.18653/v1/2023.emnlp-main.255
- https://aclanthology.org/2023.emnlp-main.255.pdf
- OA Status
- gold
- Cited By
- 14
- References
- 43
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4389518764
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Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4389518764Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.18653/v1/2023.emnlp-main.255Digital Object Identifier
- Title
-
The Art of SOCRATIC QUESTIONING: Recursive Thinking with Large Language ModelsWork title
- Type
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articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
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2023Year of publication
- Publication date
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2023-01-01Full publication date if available
- Authors
-
Jingyuan Qi, Zhiyang Xu, Ying Shen, Min‐Qian Liu, Di Jin, Qifan Wang, Lifu HuangList of authors in order
- Landing page
-
https://doi.org/10.18653/v1/2023.emnlp-main.255Publisher landing page
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https://aclanthology.org/2023.emnlp-main.255.pdfDirect link to full text PDF
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YesWhether a free full text is available
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goldOpen access status per OpenAlex
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https://aclanthology.org/2023.emnlp-main.255.pdfDirect OA link when available
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Socratic method, Socratic questioning, Computer science, Process (computing), Cognitive science, Qualitative reasoning, Artificial intelligence, Epistemology, Theoretical computer science, Programming language, Psychology, PhilosophyTop concepts (fields/topics) attached by OpenAlex
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14Total citation count in OpenAlex
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2025: 10, 2024: 4Per-year citation counts (last 5 years)
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10Other works algorithmically related by OpenAlex
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