Self-Refine: Iterative Refinement with Self-Feedback, Aman Madaan, Niket Tandon, Prakhar Gupta, Skyler Hallinan, Luyu Gao, Sarah Wiegreffe, Uri Alon, Nouha Dziri, Shrimai Prabhumoye, Yiming Yang, Shashank Gupta, Bodhisattwa Prasad Majumder, Katherine Hermann, Sean Welleck, Amir Yazdanbakhsh, Peter Clark, 2023arXiv preprint arXiv:2303.17651DOI: 10.48550/arXiv.2303.17651 - Presents a framework for LLMs to iteratively refine their own outputs using self-generated feedback, directly aligning with the concept of an iterative refinement cycle.
Designing Machine Learning Systems, Chip Huyen, 2022 (O'Reilly Media) - Provides practical guidance on MLOps practices such as experiment tracking, version control, and continuous evaluation, essential for systematic iterative data refinement.