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Hi there,
I was deeply impressed after reading your excellent paper.
I have a question regarding the creation of the wordset in Figure 5.
To generate the wordset, I utilized word_embedding (size: (32000, 4096)) and source_embedding (size: (num_tokens, 4096)). Using FAISS, I performed similarity comparisons by comparing a single source (1, 4096) with all word_embedding entries, extracting only the top 10 most similar words. This process was repeated for all num_tokens.
After training for more than 100 epochs and comparing the wordsets across all epochs, I noticed that the extracted wordsets mostly consist of meaningless special characters and words. Could you kindly explain how the wordset was extracted in your work?
Thank you.
The text was updated successfully, but these errors were encountered:
Hi there,
I was deeply impressed after reading your excellent paper.
I have a question regarding the creation of the wordset in Figure 5.
To generate the wordset, I utilized word_embedding (size: (32000, 4096)) and source_embedding (size: (num_tokens, 4096)). Using FAISS, I performed similarity comparisons by comparing a single source (1, 4096) with all word_embedding entries, extracting only the top 10 most similar words. This process was repeated for all num_tokens.
After training for more than 100 epochs and comparing the wordsets across all epochs, I noticed that the extracted wordsets mostly consist of meaningless special characters and words. Could you kindly explain how the wordset was extracted in your work?
Thank you.
The text was updated successfully, but these errors were encountered: