Papers by XinLong Zhao

1 papers
Rethinking Data Mixing from the Perspective of Large Language Models (2026.acl-short)

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Challenge: Existing methods to mix data with LLMs have relied on domain definitions derived from intuition.
Approach: They propose a reweighting framework that restructures data scheduling as a graph-constrained optimization problem.
Outcome: The proposed framework achieves competitive performance on GPT-2 models.

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