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First of all, I would like to commend you on your excellent work. I have a few questions while using your code:
I noticed that in the command line arguments, the parameter alpha controls the weight of the skip-gram loss. If it is set to 0, does it mean that the skip-gram pretraining is not used? If so, does the model still obtain initial embeddings in this case?
Could you please clarify the purpose of add_padding_idx? Is it designed for non-uniform hypergraphs? For example, my hypergraph contains both 2-edge and 3-edge relations.
Looking forward to your reply. Thank you!
The text was updated successfully, but these errors were encountered:
Dear Author,
First of all, I would like to commend you on your excellent work. I have a few questions while using your code:
I noticed that in the command line arguments, the parameter alpha controls the weight of the skip-gram loss. If it is set to 0, does it mean that the skip-gram pretraining is not used? If so, does the model still obtain initial embeddings in this case?
Could you please clarify the purpose of add_padding_idx? Is it designed for non-uniform hypergraphs? For example, my hypergraph contains both 2-edge and 3-edge relations.
Looking forward to your reply. Thank you!
The text was updated successfully, but these errors were encountered: