mlsanityData to 7 Oct 2026

P-CoT: A Pedagogically-motivated Participatory Chain-of-Thought Prompting for Phonological Reasoning in LLMs

arXiv 2507.16656 ↗First posted 22 Jul 2025cs.CLcited by 0

On the map: LLM reasoning → Prompting and chain-of-thought reasoning

Abstract (arXiv)

This study explores the potential of phonological reasoning within text-based large language models (LLMs). Utilizing the PhonologyBench benchmark, we assess tasks like rhyme word generation, g2p conversion, and syllable counting. Our evaluations across 12 LLMs reveal that while few-shot learning offers inconsistent gains, the introduction of a novel Pedagogically-motivated Participatory Chain-of-Thought (P-CoT) prompt, which is anchored in educational theories like scaffolding and discovery learning, consistently enhances performance. This method leverages structured guidance to activate latent phonological abilities, achieving up to 52% improvement and even surpassing human baselines in certain tasks. Future work could aim to optimize P-CoT prompts for specific models or explore their application across different linguistic domains.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Placed in Prompting and chain-of-thought reasoning, one of 17 directions in LLM reasoning. Builds on 28 of its 60 references that are in the map. First posted on arXiv 22 Jul 2025.

Builds on

28 of 60 references.

References · 28

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16 more
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  1. 2025Audio-CoT: Exploring Chain-of-Thought Reasoning in Large Audio Language Model
  2. 2023Stress Testing Chain-of-Thought Prompting for Large Language Models
  3. 2025Short-Path Prompting in LLMs: Analyzing Reasoning Instability and Solutions for Robust Performance
  4. 2023Towards Better Chain-of-Thought Prompting Strategies: A Survey
  5. 2024Enhancing Chain of Thought Prompting in Large Language Models via Reasoning Patterns
  6. 2025What Really Counts? Examining Step and Token Level Attribution in Multilingual CoT Reasoning
  7. 2022Text and Patterns: For Effective Chain of Thought, It Takes Two to Tango
  8. 2022Towards Understanding Chain-of-Thought Prompting: An Empirical Study of What Matters