Papers by Mengyi Yan
PUER: Boosting Few-shot Positive-Unlabeled Entity Resolution with Reinforcement Learning (2025.findings-emnlp)
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| Challenge: | Existing approaches to entity resolution focus on supervised learning, but manual annotation is labor-intensive. |
| Approach: | They propose an end-to-end ER solution that leverages Large Language Models in PU learning setting to address low-resource entity resolution. |
| Outcome: | The proposed solution improves the performance of PUER on a positive-unlabeled learning environment. |