Papers by DongWang DongWang

1 papers
Logical DA: Enhancing Data Augmentation for Logical Reasoning via a Multi-Agent System (2025.findings-acl)

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Challenge: Existing data augmentation paradigms isolate data synthesis from label validation, thereby reducing their utility for complex reasoning tasks.
Approach: They propose a framework for enhancing reasoning-focused data augmentation in few-shot learning scenarios that integrates four agents through two synergistic phases: diverse data generation and label verification.
Outcome: The proposed framework achieves the highest average improvement in task accuracy in both fine-tuning and in-context learning paradigms.

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