Papers by Zhenlin Hu

1 papers
Logical Structure as Knowledge: Enhancing LLM Reasoning via Structured Logical Knowledge Density Estimation (2026.findings-acl)

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Challenge: Existing data-centric paradigms equate quality with factuality or diversity and ignore the internal logical complexity of training samples.
Approach: They propose a density-aware re-cognizing optimization strategy that prioritizes high-density logical samples to align training with the model's reasoning boundary.
Outcome: The proposed metric outperforms existing methods and improves reasoning performance without increasing total data volume.

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