In the code, there is a mention about "cosine similarity from BERT-based embeddings but observed longer inference time and
similar performance", and this version of code is using SBRT similarity, which is missing "from Layer2.Fine_tuned_BERT import get_similarity_from_SBERT" file.
In the code, there is a mention about "cosine similarity from BERT-based embeddings but observed longer inference time and similar performance", and this version of code is using SBRT similarity, which is missing "from Layer2.Fine_tuned_BERT import get_similarity_from_SBERT" file.
So in order to implement the paper settings, we need to replace this sbert similarity function to LDA similarity function. ( https://github.com/DRSY/DGen/blob/ddbe0e47080bb9ec9335e93ea8993ef410ba9cd7/Conceptualizer.py#L68 -> https://github.com/DRSY/DGen/blob/ddbe0e47080bb9ec9335e93ea8993ef410ba9cd7/Conceptualizer.py#L169 ) The code is fragmented, but it seems to contain all the important information. Thank you for providing codes for feature similarity calculation