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Edge 365: Understanding LLM Reasoning with Reflexion

Edge 365: Understanding LLM Reasoning with Reflexion

A deep dive into one of the most complete LLM reasoning methods.

Jan 30, 2024
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Edge 365: Understanding LLM Reasoning with Reflexion
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A futuristic scene depicting a cool, advanced artificial intelligence language model, visualized as a sleek, metallic humanoid robot with glowing circuit patterns on its body. The robot is sitting at a modern, holographic desk, with floating holographic screens showing complex algorithms and equations. It's deep in thought, with a focused expression, analyzing the problem. The background is a high-tech lab with advanced computers and digital displays, illustrating the breakdown of a complex problem into logical steps. The atmosphere is illuminated with soft blue and green lights, highlighting the robot's contemplation.
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In this Issue:

  1. An overview of the Reflexion reasoning method in LLMs.

  2. A review the original Reflexion paper by Northeastern University.

  3. An introduction to Flowise, a visual tool for building LLM apps.

💡 ML Concept of the Day: What is Reflexion?

In the past issue of our series about LLM reasoning, we introduced ReAct as a method that can combine reasoning and action in a single loop. Today, we would like to explore a method that follows similar principles enable LLM agents to execute actions. Reflexion tries to address some of the limitations of other reasoning methods in this area that relied on massive models which limits the potential actions to in-context examples given that everything else will take substantial compute time.

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