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2025 ICML ICML 2025

Collapse or Thrive: Perils and Promises of Synthetic Data in a Self-Generating World

Abstract

No abstract available. No abstract was captured for this paper when its proceedings were scraped - most often an older edition published without one online. How the corpus is built.

Authors

Joshua Kazdan, Rylan Schaeffer, Apratim Dey, Matthias Gerstgrasser, Rafael Rafailov, David L. Donoho, Sanmi Koyejo

Topics

Machine Learning > Optimization & Theory > Optimization Deep Learning > Models > Generative Models Artificial Intelligence > Core AI > Large Language Models

Keywords

pretraining kernel density estimation generative model synthetic data model collapse language model fine-tuning
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