Papers by Ruhui Ma
TKGT: Redefinition and A New Way of Text-to-Table Tasks Based on Real World Demands and Knowledge Graphs Augmented LLMs (2024.emnlp-main)
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| Challenge: | Existing studies focus on text-to-table tasks that ignore domain structures and use simple datasets to extract structured information from unstructured text. |
| Approach: | They propose a new text-to-table task that generates domain knowledge graphs from raw text using a mixed-IE method and a hybrid retrieval augmented generation method. |
| Outcome: | The proposed dataset improves compatibility with long text-processing tasks by incorporating domain knowledge graphs (KGs) classes into tables. |
TST: A Schema-Based Top-Down and Dynamic-Aware Agent of Text-to-Table Tasks (2025.acl-long)
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| Challenge: | Existing methods to extract text content based on static table structures neglect to deal with precise inner-document evidence extraction and dynamic information such as multiple entities and events. |
| Approach: | They propose a dynamic content extraction agent framework that uses type recognition to extract context evidences with the conduction of domain schema sequentially. |
| Outcome: | The proposed framework exhibits state-of-the-art (SOTA) performance on a large dataset. |