Skip to main content

All Questions

Filter by
Sorted by
Tagged with
1 vote
3 answers
438 views

How to improve language model ex: BERT on unseen text in training?

so I am using pre-trained language model for binary classification. I fine-tune the model by training on data my downstream task. The results are good almost 98% F-measure. However, when I remove a ...
Injy Sarhan's user avatar
1 vote
1 answer
206 views

How does clustering improve a language model?

This article describes a hierarchical clustering algorithm which clusters the words within a vocabulary based on their similarity, in order to improve a language model (in the article, n-grams). How ...
Hello Lili's user avatar
1 vote
1 answer
511 views

Curse of dimensionality with language models

In the seminal paper A Neural Probabilistic Language Model, Yoshua Bengio and his colleagues make the following point: If one wants to model the joint probability distribution of 10 consecutive ...
Antoine's user avatar
  • 6,217
7 votes
2 answers
6k views

Does trigram guarantee to perform more accurately than bigram?

When implementing some NLP project, such as text segmentation, Name Entity Recognition, does using trigram guarantee to perform more accurately than bigram? $$ Trigram: p(s_t\mid s_{t-2}, s_{t-1}) $$...
xiaoyao's user avatar
  • 405
11 votes
3 answers
16k views

Regarding using bigram (N-gram) model to build feature vector for text document

A traditional approach of feature construction for text mining is bag-of-words approach, and can be enhanced using tf-idf for setting up the feature vector characterizing a given text document. At ...
user3125's user avatar
  • 3,089