Papers by Yixuan Nan
EA-Agent: A Structured Multi-Step Reasoning Agent for Entity Alignment (2026.acl-long)
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| Challenge: | Entity alignment (EA) aims to identify entities across different knowledge graphs (KGs) that refer to the same real-world object. |
| Approach: | They propose to use large language models to integrate semantic knowledge into EA to identify entities across different knowledge graphs that refer to the same object. |
| Outcome: | The proposed agent outperforms existing methods and achieves state-of-the-art performance on three benchmark datasets. |
CMMLU: Measuring massive multitask language understanding in Chinese (2024.findings-acl)
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| Challenge: | Existing large language models struggle to achieve an accuracy of even 60%, which is the pass mark for Chinese exams. |
| Approach: | They propose to use CMMLU to evaluate Chinese multilingual and Chinese LLMs in a comprehensive benchmark that covers various subjects and settings. |
| Outcome: | The proposed benchmark covers natural sciences, social sciences, engineering, and the humanities and aims to improve on existing models. |