Non-Interactive Symbolic-Aided Chain-of-Thought for Logical Reasoning

• URL: http://arxiv.org/abs/2508.12425v2
• Date: Sat, 04 Oct 2025 17:29:03 GMT
• Title: Non-Interactive Symbolic-Aided Chain-of-Thought for Logical Reasoning
• Authors: Phuong Minh Nguyen, Tien Huu Dang, Naoya Inoue,
• Abstract summary: Symbolic-Aided Chain-of-Thought (CoT) is an improved approach to logical reasoning in large language models (LLMs)<n>CoT integrates lightweight symbolic representations into few-shot prompts.<n>Experiments on four well-known logical reasoning benchmarks demonstrate the effectiveness of the proposed approach.
• Score: 4.839520296557773
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: This work introduces Symbolic-Aided Chain-of-Thought (CoT), an improved approach to standard CoT, for logical reasoning in large language models (LLMs). The key idea is to integrate lightweight symbolic representations into few-shot prompts, structuring the inference steps with a consistent strategy to make reasoning patterns more explicit within a non-interactive reasoning process. By incorporating these symbolic structures, Symbolic-Aided CoT preserves the generalizability of standard prompting techniques while enhancing the transparency, interpretability, and analyzability of LLM logical reasoning. Extensive experiments on four well-known logical reasoning benchmarks -- ProofWriter, FOLIO, ProntoQA, and LogicalDeduction, which cover diverse reasoning tasks and scenarios -- demonstrate the effectiveness of the proposed approach, particularly in complex reasoning tasks that require navigating multiple constraints or rules. Notably, Symbolic-Aided CoT consistently improves LLMs' reasoning capabilities across various model sizes and significantly outperforms conventional CoT on three out of four datasets, ProofWriter, ProntoQA, and LogicalDeduction.

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