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title: README
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ContinuousBench
ContinuousBench measures progress in differentially private synthetic data.
ContinuousBench has two tracks:
Both datasets:
- are designed to contain completely new information that models cannot answer
- are paired with QA that can only be answered after training on the corpus
Generate a DP synthetic version of News or Geminon, then test it: https://github.com/plau666/ContinuousBenchEval.
Our evaluation trains a model on your DP synthetic version, and then asks the paired QA to see if your DP synthetic data was capable of teaching a model the knowledge present in the original corpus.