Papers by Zhenzi Li
Leveraging Estimated Transferability Over Human Intuition for Model Selection in Text Ranking (2024.emnlp-main)
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| Challenge: | Existing methods for text ranking are based on intuition, but their estimated transferability may not align well with the objectives of text ranking. |
| Approach: | They propose to compute expected rank as transferability, explicitly reflecting the model’s ranking capability. |
| Outcome: | The proposed method shows significant improvements over previous classification-oriented TE methods, human intuition, and ChatGPT with minor time consumption. |
Modelling Long-distance Node Relations for KBQA with Global Dynamic Graph (2020.coling-main)
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| Challenge: | Existing studies rely on deep graph neural networks (GNNs) to capture rich structural information, but they lack the structural information needed for QA. |
| Approach: | They propose a framework which captures structural information from KBs and models long-distance node relations from two perspectives. |
| Outcome: | The proposed framework models long-distance node relations from two perspectives . it is based on two widely used multi-hop KBQA datasets . |