SELF-REFINE — A New Milestone in the AI Era?

Isaac Kargar
6 min readApr 4, 2023

Note: ChatGPT is used in this post as an assistant.

When I found this work, I got super excited! A bunch of questions came to my mind, and I knew I had to write a blog post on it. It might be a game-changer like the Transformer paper was. This could take AI to new levels. So, let’s jump in and see what this paper’s all about.

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Introduction

Large language models (LLMs) can produce coherent outputs, but they often struggle with more complex tasks that involve multiple objectives or less-defined goals. Current advanced techniques for refining LLM-generated text rely on external supervision and reward models, which require significant amounts of training data or costly human annotations. This highlights the need for a more flexible and effective method that can handle a range of tasks without extensive supervision.

To address these limitations, a new method called SELF-REFINE has been proposed. It better mimics the human creative generation process without the need for an expensive human feedback loop. SELF-REFINE consists of an iterative loop between two components, FEEDBACK and REFINE, that work together to produce high-quality outputs. The process starts with an initial draft output generated by a model, which is then passed back to the same model for feedback and refinement. This…

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Isaac Kargar
Isaac Kargar

Written by Isaac Kargar

Co-Founder and Chief AI Officer @ Resoniks | Ph.D. candidate at the Intelligent Robotics Group at Aalto University | https://kargarisaac.github.io/

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