"MyGO Multiplex CoT: A Method for Self-Reflection in Large Language Models via Double Chain of Thought Thinking"

Double the thought, double the smarts: Multiplex CoT for LLMs.

Multiplex CoT enhances LLM reasoning by prompting self-reflection through a double chain of thought.

This iterative process refines initial reasoning, leading to more coherent and accurate outputs.

-----

Paper - https://arxiv.org/abs/2501.13117

Original Problem 😞:

→ LLMs struggle with consistent logical reasoning and self-reflection in complex scenarios.

-----

Solution in this Paper 🤔:

→ Multiplex CoT involves two stages of Chain of Thought.

→ First, the LLM generates an initial chain of reasoning to answer a prompt.

→ Second, the LLM reviews and critiques its initial reasoning in a second chain of thought.

→ This second stage identifies inconsistencies or flaws, leading to a refined final answer.

-----

Key Insights from this Paper 💡:

→ Mimicking human self-reflection improves LLM reasoning.

→ Iterative refinement enhances logical coherence and accuracy.

→ Prompt engineering enables self-reflection without model retraining.

-----

Results 💯:

→ Multiplex CoT improved logical consistency by 7% in arithmetic problem-solving.

→ Error correction rate reached 15% in the same task.

→ On other tasks, it showed 9-10% improvements in logical consistency and 12-20% error correction rates.