R-GDA: Reflective Guidance Data Augmentation with Multi-Agent Feedback for Domain-Specific Named Entity Recognition (2026.findings-eacl)
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| Challenge: | Named Entity Recognition (NER) tasks require data augmentation due to the scarcity of annotated corpora. |
| Approach: | They propose a framework that introduces a multi-agent feedback loop to enhance augmentation quality. |
| Outcome: | The proposed framework improves on SciERC and NCBI-disease datasets and achieves low BERTScore in most cases. |
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Dong-Ho Lee, Ravi Kiran Selvam, Sheikh Muhammad Sarwar, Bill Yuchen Lin, Fred Morstatter, Jay Pujara, Elizabeth Boschee, James Allan, Xiang Ren
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