-
Dear experts,
I recently stumbled upon the Skip-Thought paper and found it extremely interesting. I have managed to train a small model using some 2.7 million sentences for testing purposes. My pr…
-
Hello @giannisnik, I was wondering whether we can apply the models here to samples that can be represented with multiple sets. For instance, document representation with each sentence as a bag. Thanks…
-
The document says:
> This canonical representation is used for digital signature purposes, transmission, etc.
What is "etc." here? this is nearly the most important sentence of the document: wh…
-
## Adding a Dataset
- **Name:** *eHealth-KD 2019*
- **Description:** *The representation model used in eHealth-KD 2019 [20] allows the representation of concepts and their interrelation, oblivious o…
-
For sequence encoding tasks like NLI and NMT, the encoder gives vector representation for sentence. My doubt is that, are we supposed to use pre-trained embeddings of words to get these sentence embed…
-
I'm using using BERTopic 0.16.2 and I'm trying to understand why about a third of my documents are categorized as outliers. `len(docs)` is 7578 and the number of documents in my largest topics are
`…
-
You wrote this in your representation method:
`return author + average_sentence_length`
Technically, you are trying to add a string to an integer, which will return no value. I would suggest ret…
-
Hi,
I want to check if combination with tf-idf weights and tokens embeddings is better representation for my use case/data(I would love to know what you think about it).
Searching for implementation…
-
hello kim. I have an issue about the size of feature map when reading your paper.
In your paper, you had used two filters with windows size in 2 and 3. And the representation matrix size of sentence …
-
Hello, as a beginner in NLP analysis I am trying to figure out how to use the sentence embeddings of Sbert for a sentence classification task. From the description [here](https://www.sbert.net/docs/tr…
zsun9 updated
2 years ago