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Self-Refine is a framework for iteratively improving outputs from LLMs through a process of iterative creation with feedback
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Self-Refine: Iterative Refinement with Self-Feedback Self-Refine: Iterative Refinement with Self-Feedback Aman Madaan 1 , Niket Tandon 2 , Prakhar Gupta 1 , Skyler Hallinan 3 , Luyu Gao 1 , Sarah Wiegreffe 2 , Uri Alon 1 , Nouha Dziri 2 , Shrimai Prabhumoye 4 , Yiming Yang 1 , Sean Welleck 2,3 , Bodhisattwa Prasad Majumder 5 , Shashank Gupta 2 Amir Yazdanbakhsh 6 , Peter Clark 2 1 Language Technologies Institute, Carnegie Mellon University 2 Allen Institute for AI, 3 University of Washington, 4 NVIDIA, 5 UC San Diego 6 Google Research, Brain Team Paper Code Demo Self-Refine is a novel approach that allows LLMs to iteratively refine outputs and incorporate feedback along multiple dimensions to improve performance on diverse tasks. Unlike prior work, it does not require supervised...
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