chain-of-thought ↔ prompt engineering

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related 2.81 — strongly supporting 6 facts

Chain-of-thought is a specific technique within the broader field of prompt engineering, as evidenced by its inclusion in various prompt engineering protocols and frameworks [1], [2], and [3]. Furthermore, research demonstrates that chain-of-thought prompting is a key method used to improve model reasoning and reduce hallucinations within the practice of prompt engineering [4], [5].

Facts (6)

Sources

Survey and analysis of hallucinations in large language models frontiersin.org Frontiers 3 facts

claimPrompt engineering, particularly Chain-of-Thought (CoT) prompting, reduces hallucination rates in large language models but is not universally effective.

measurementStructured prompting using Chain-of-Thought reduced CPS values to 0.06, demonstrating the effectiveness of structured prompt engineering as noted by Zhou et al. (2022).

procedureThe prompt engineering protocol used in the study involves five categories: Zero-shot (basic instruction), Few-shot (2-3 input-output examples), Instruction (structured natural language), Chain-of-thought (step-by-step reasoning), and Vague/misleading (intentionally unclear).

KG-RAG: Bridging the Gap Between Knowledge and Creativity - arXiv arxiv.org arXiv 2 facts

claimPrompt engineering techniques, including Chain of Thought (CoT), Tree of Thought (ToT), Graph of Thoughts (GoT), and ReAct (Reason and Act), have demonstrated significant improvements in the reasoning abilities and task-specific actions of Large Language Models.

Unlocking the Potential of Generative AI through Neuro-Symbolic ... arxiv.org arXiv 1 fact

claimPrompt engineering techniques, including Chain-of-Thought (CoT) prompting, zero-shot prompting, and few-shot prompting, enable Large Language Models (LLMs) to reason and generalize across diverse tasks without requiring extensive retraining.