Papers by Lior Belenki

1 papers
Optimizing Pre-Training Data Mixtures with Mixtures of Data Expert Models (2025.acl-long)

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Challenge: Existing methods to optimize language model pre-training data mixtures are difficult due to the complexity of the data mixture.
Approach: They propose a method to optimize language model pre-training data mixtures by approximating cross-entropy loss via a Mixture of Data Experts (MDE).
Outcome: The proposed method improves performance on a slimPajama dataset with a mixture of data experts.

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