Papers by Shangyi Geng
Graph Hawkes Transformer for Extrapolated Reasoning on Temporal Knowledge Graphs (2022.emnlp-main)
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| Challenge: | Existing methods for entity prediction cannot predict when an event will occur . there are many facts not related to the query that can confuse the model . |
| Approach: | They propose a temporal knowledge Graph reasoning model based on Graph Hawkes Transformer . the model captures instantaneous structural and temporal evolution information . |
| Outcome: | The proposed model performs much better under long-term evolution scenarios. |
Great Memory, Shallow Reasoning: Limits of kNN-LMs (2025.naacl-short)
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| Challenge: | Existing models trained on poor quality data have shown strong performance in language modeling and some downstream benchmarks. |
| Approach: | They evaluate kNN-LMs on a diverse set of tasks and evaluate their performance. |
| Outcome: | The proposed extension could improve on a variety of tasks, but it fails to perform on reasoning tasks that require integrating multiple pieces of information. |