Comments (3)
By the way, I am wondering why the model with 2-hop filtering performed so good but you didn't take it as the baseline?
We wanted to focus on the incomplete KG setting where our model outperforms the others (in MetaQA). In such cases, neighbourhood filtering is not a good option since we may miss out on answer nodes due to graph incompleteness. So we reported our result as the one without neighbourhood filtering. As you can see in the ablation study, on the incomplete graph, the model with 2-hop filtering performs worse than the one without filtering, reaffirming our point.
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Can you try to use parameter --relation_dim 128 and let me know the results?
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Can you try to use parameter --relation_dim 128 and let me know the results?
Thanks, I tried the parameter and got:
'webqsp_full hop Validation accuracy (no relation scoring) increased from previous epoch 0.5425048669695003' after 6 epochs of training.
By the way, I am wondering why the model with 2-hop filtering performed so good but you didn't take it as the baseline?
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Related Issues (20)
- relation in fbwq_full
- relation matching
- MetaQA relation match HOT 1
- About ComplEx score calculation HOT 1
- The MetaQA dataset HOT 2
- Question with "half KG" protocol HOT 2
- How to build your own pruning_ train.txt
- Hello I have some questiones about the code such as what is the meaning of "best_valid" HOT 1
- Do you use the folder "train_embeddings"?
- I have some question in the relation matching
- When I run RoBERTa / main.py, running to ' creating model ' GPU takes up 0 and takes several hours to create the model.
- Is it possible to share the pdf version or ppt version slides
- How to use eval? How can I use pre trained model for QA? HOT 1
- RoBERTa used for question embedding
- Pretrained models missing HOT 1
- How to set up fbwq_full?
- miss files HOT 2
- About dataset
- pretrained_models.zip HOT 7
- No found pretrained_model
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