Papers by Ma Zerun

1 papers
MIG: Automatic Data Selection for Instruction Tuning by Maximizing Information Gain in Semantic Space (2025.findings-acl)

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Challenge: Existing methods for instruction-tuning datasets prioritize instance quality and use heuristic rules to maintain diversity.
Approach: They propose a method that quantifies diversity based on the distribution of information within a label graph.
Outcome: The proposed method outperforms state-of-the-art methods on 5% Tulu3 datasets and base models.

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