Google Research Reveals Prompt Engineering Techniques That Double LLM Reasoning Accuracy

20.01.2026

Researchers at Google have published findings demonstrating methods to enhance the reasoning accuracy of large language models by up to two times. The breakthrough lies in strategic prompt engineering that triggers self-correction mechanisms within AI models.

Key Techniques for Improved Model Performance:

1. Uncertainty Markers Integration
Instruct the model to incorporate hesitation phrases and self-doubt indicators during reasoning processes. This activates the model's self-correction pathways:

"During your reasoning process, use phrases like 'Wait, let me verify this', 'Oh, I may have missed...', 'But what if...'. If you identify an error in your reasoning, acknowledge it and provide a correction."

2. Multi-Perspective Problem Analysis
Prompt the model to approach problems from multiple expert viewpoints simultaneously:

"Act as a team of three experts: a skeptical critic, a creative designer, and a meticulous analyst. Discuss the solution to this problem by taking turns presenting arguments and refuting each other's errors."

3. Adversarial Self-Debate
Implement conflicting opinion frameworks to mitigate hallucinations by forcing the model to challenge its own outputs:

"First, propose a solution, then rigorously critique it by identifying weaknesses. Formulate your final answer based on this critical analysis."

4. Role-Based Character Assignment
Assign distinct personas with different cognitive approaches to enhance result quality:

"First, examine this problem from the perspective of a pedantic professor searching for factual errors. Then, approach it from the viewpoint of a bold inventor. Synthesize their conclusions."

These prompt engineering strategies leverage the inherent capabilities of LLMs to perform metacognitive operations, significantly improving reasoning accuracy and reducing the occurrence of AI hallucinations.

Source: https://arxiv.org/pdf/2601.10825

Tags: chatbots Prompt Engineering LLM AI Reasoning Google-Research

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