Papers by Yudai Pan
G-HiRel: Enhancing the Adaption to Knowledge Updating for Large Language Model Reasoning (2026.findings-acl)
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| Challenge: | Large language models (LLMs) have good performance in multiple reasoning tasks, but are limited to adapt the rapid knowledge updates in the real-world scenario. |
| Approach: | They propose an LLM reasoning framework with hierarchical relational retrieval for large-scale knowledge updating, named G-HiRel. |
| Outcome: | The proposed framework achieves superiority in terms of accuracy and interpretability on three benchmarks. |
Inductive Relation Prediction with Logical Reasoning Using Contrastive Representations (2022.emnlp-main)
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| Challenge: | Existing methods for relation prediction in knowledge graphs (KGs) are limited by the inductive setting because entities in training process are finite. |
| Approach: | They propose a graph convolutional network-based model LogCo with logical reasoning by contrastive representations that extracts subgraphs and relational paths between two entities to supply the entity-independence. |
| Outcome: | The proposed model outperforms existing methods on twelve inductive datasets. |