Papers with -shot relations
Few-Shot Multi-Hop Relation Reasoning over Knowledge Bases (2020.findings-emnlp)
Copied to clipboard
| Challenge: | Existing methods for multi-hop relation reasoning require limited data for each query relation, resulting in limited interpretation. |
| Approach: | They propose a few-shot multi-hop relation learning model that uses reinforcement learning to model sequential steps of multi-hopping reasoning and performs heterogeneous structure encoding and knowledge-aware search space pruning. |
| Outcome: | Empirical results show that the proposed model outperforms state-of-the-art models over few-shot relations. |
Adapting Meta Knowledge Graph Information for Multi-Hop Reasoning over Few-Shot Relations (D19-1)
Copied to clipboard
| Challenge: | Existing methods for multi-hop reasoning assume that every relation has enough triples for training . however, performance drops significantly on few-shot relations . |
| Approach: | They propose a meta-based multi-hop reasoning method that learns meta parameters from high-frequency relations that could quickly adapt to few-shot scenarios. |
| Outcome: | The proposed method outperforms state-of-the-art methods in few-shot scenarios on two public datasets from Freebase and NELL. |
Few-shot Link Prediction on Hyper-relational Facts (2024.lrec-main)
Copied to clipboard
| Challenge: | Existing methods to predict missing elements in hyper-relational facts require high-quality data. |
| Approach: | They propose a task to predict a missing entity in a hyper-relational fact with limited support instances. |
| Outcome: | The proposed model outperforms existing models on three datasets. |