Papers by Kerui Zhu
Chinese SafetyQA: A Safety Short-form Factuality Benchmark for Large Language Models (2025.acl-long)
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Yingshui Tan, Boren Zheng, Baihui Zheng, Kerui Cao, Huiyun Jing, Jincheng Wei, Jiaheng Liu, Yancheng He, Wenbo Su, Xiaoyong Zhu, Bo Zheng, Kaifu Zhang
| Challenge: | Large language models have created significant safety concerns . factuality ability is crucial in determining whether they can be deployed and applied safely and compliantly within specific regions. |
| Approach: | They propose a benchmark to evaluate the factuality of large language models in China . they evaluate the models' ability to provide accurate and reliable information . |
| Outcome: | The proposed benchmark evaluates the factuality abilities of existing LLMs and compares them to LLM abilities. |
Descriptive Knowledge Graph in Biomedical Domain (2023.emnlp-demo)
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| Challenge: | Existing systems that retrieve unconnected passages do not provide efficient search for relational knowledge. |
| Approach: | They propose a system that automatically extracts and generates informative and descriptive sentences from the biomedical corpus and facilitates efficient search for relational knowledge. |
| Outcome: | The proposed system extracts and generates informative and descriptive sentences from the biomedical corpus and facilitates the efficient search for relational knowledge. |
DEER: Descriptive Knowledge Graph for Explaining Entity Relationships (2022.emnlp-main)
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| Challenge: | Existing knowledge graphs lack two desired features for modeling entity relationships: openness and informativeness. |
| Approach: | They propose a self-supervised learning method to extract relation descriptions with the analysis of dependency patterns and generate relation descriptions using a transformer-based relation description synthesizing model. |
| Outcome: | The proposed system extracts and generates high-quality relation descriptions without human labeling. |
DimonGen: Diversified Generative Commonsense Reasoning for Explaining Concept Relationships (2023.acl-long)
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| Challenge: | Existing models that describe concepts in everyday situations are difficult to summarize in a single sentence. |
| Approach: | They propose DimonGen, which generates sentences describing concept relationships in everyday scenarios. |
| Outcome: | The proposed model outperforms baseline models in terms of quality and diversity of generated sentences. |