Papers by Wenkun Zhang
Prompting ChatGPT in MNER: Enhanced Multimodal Named Entity Recognition with Auxiliary Refined Knowledge (2023.findings-emnlp)
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| Challenge: | Existing methods to enhance textual entity prediction neglect the need for external knowledge or encounter high redundancy in the retrieved knowledge. |
| Approach: | They propose a framework that leverages ChatGPT as an implicit knowledge base and heuristically generates auxiliary knowledge for more efficient entity prediction. |
| Outcome: | The proposed framework outperforms state-of-the-art methods on two classic datasets and exhibits a stronger robustness and generalization capability. |
LLMs as Bridges: Reformulating Grounded Multimodal Named Entity Recognition (2024.findings-acl)
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| Challenge: | Existing methods for Grounded Multimodal Named Entity Recognition (GMNER) lack a strong correlation between image-text pairs and is ungroundable. |
| Approach: | They propose a framework that reformulates GMNER into a joint MNER-VE-VG task by leveraging large language models as a connecting bridge. |
| Outcome: | The proposed framework outperforms state-of-the-art methods on the existing GMNER dataset and achieves absolute leads of 10.65%, 6.21%, and 8.83% in all three subtasks. |