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Focused ReAct: Improving ReAct through Reiterate and Early Stop

Shuoqiu Li, Han Xu, Haipeng Chen

TL;DR

Focused ReAct is introduced, an enhanced version of the ReAct paradigm that incorporates reiteration and early stop mechanisms that help the model stay focused on the original query and avoid repetitive behaviors.

Abstract

Large language models (LLMs) have significantly improved their reasoning and decision-making capabilities, as seen in methods like ReAct. However, despite its effectiveness in tackling complex tasks, ReAct faces two main challenges: losing focus on the original question and becoming stuck in action loops. To address these issues, we introduce Focused ReAct, an enhanced version of the ReAct paradigm that incorporates reiteration and early stop mechanisms. These improvements help the model stay focused on the original query and avoid repetitive behaviors. Experimental results show accuracy gains of 18% to 530% and a runtime reduction of up to 34% compared to the original ReAct method.

Focused ReAct: Improving ReAct through Reiterate and Early Stop

TL;DR

Focused ReAct is introduced, an enhanced version of the ReAct paradigm that incorporates reiteration and early stop mechanisms that help the model stay focused on the original query and avoid repetitive behaviors.

Abstract

Large language models (LLMs) have significantly improved their reasoning and decision-making capabilities, as seen in methods like ReAct. However, despite its effectiveness in tackling complex tasks, ReAct faces two main challenges: losing focus on the original question and becoming stuck in action loops. To address these issues, we introduce Focused ReAct, an enhanced version of the ReAct paradigm that incorporates reiteration and early stop mechanisms. These improvements help the model stay focused on the original query and avoid repetitive behaviors. Experimental results show accuracy gains of 18% to 530% and a runtime reduction of up to 34% compared to the original ReAct method.

Paper Structure

This paper contains 6 sections, 2 figures, 2 tables.

Table of Contents

  1. Introduction
  2. Methodology
  3. Reiterate to Solve Context Loss
  4. Early Stop to Prevent Action Repetition
  5. Experimentation
  6. Conclusion

Figures (2)

  • Figure 1: The yellow highlighted region illustrates where the model loses focus on the original question, while the red highlighted region depicts repeated actions that result in a failed response.
  • Figure 2: The QA process by Focused ReAct for the same question, which applies reiteration (highlighted in yellow) and early stop (highlighted in red) to resolve the context loss and the repeated action issue.