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Overview

How can we improve the faithfulness of reasoning chains generated by Language Models? Faithful Chain of Thought improves the faithfulness of reasoning chains by breaking it up into two stages:
  1. Translation: Translate a user query into a series of reasoning steps - task-specific steps that can be executed deterministically
  2. Problem Solving: Execute steps and arrive at a final answer that is consistent with the reasoning steps
Examples of task-specific systems:
  • Math Word Problems: PHP code that can be evaluated to derive a final answer
  • Multi-Hop QA: Multi-step reasoning process using programming logic
  • Planning: Generate symbolic goals and use planning systems to solve queries

Example

References

  1. Faithful Chain-of-Thought Reasoning