Papers by Mingkang Zhu

1 papers
Enhancing LLM Knowledge Learning through Generalization (2025.findings-emnlp)

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Challenge: Continued pre-training on paraphrased data has shown empirical promise for enhancing knowledge acquisition, but this approach is costly and unreliable as it relies on external models or manual effort for rewriting.
Approach: They propose formatting-based data augmentation which diversifies documents conveying the same knowledge by altering document formats rather than their content.
Outcome: The proposed methods improve generalization to diverse paraphrased contexts and enhance pre-training and instruction tuning.

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