<ul><li>IR2, Information Regularization for Information Retrieval, is a technique for reducing overfitting during synthetic data generation in settings with limited training data.</li><li>Experimental results indicate that IR2 outperforms previous synthetic query generation methods and reduces cost by up to 50%.</li><li>Three different regularization methods at different stages of the query synthesis pipeline are explored, offering varying degrees of performance improvement.</li><li>The code, prompts, and synthetic data for IR2 are available on GitHub.</li></ul>

IR2: Information Regularization for Information Retrieval

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