Definition of downstream tasks in NLP
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What does downstream tasks terminology mean in NLP? I saw this terminology used in several articles but I can't understand the idea behind it.
nlp
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What does downstream tasks terminology mean in NLP? I saw this terminology used in several articles but I can't understand the idea behind it.
nlp
add a comment |
up vote
0
down vote
favorite
up vote
0
down vote
favorite
What does downstream tasks terminology mean in NLP? I saw this terminology used in several articles but I can't understand the idea behind it.
nlp
What does downstream tasks terminology mean in NLP? I saw this terminology used in several articles but I can't understand the idea behind it.
nlp
nlp
asked Nov 11 at 12:38
KF2
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6,70962869
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1 Answer
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Basically anything you might want to do with the results of NLP.
From the intro of one recent article from the arxiv by Christian S. Perone, Roberto Silveira, and Thomas S. Paula:
Word embeddings are nowadays pervasive on a wide spectrum of Natural Language Processing (NLP) and Natural Language Understanding (NLU) applications. These word representations improved downstream tasks in many domains such as machine translation, syntactic parsing, text classification, and machine comprehension, among other
to list a few example domains.
add a comment |
1 Answer
1
active
oldest
votes
1 Answer
1
active
oldest
votes
active
oldest
votes
active
oldest
votes
up vote
1
down vote
Basically anything you might want to do with the results of NLP.
From the intro of one recent article from the arxiv by Christian S. Perone, Roberto Silveira, and Thomas S. Paula:
Word embeddings are nowadays pervasive on a wide spectrum of Natural Language Processing (NLP) and Natural Language Understanding (NLU) applications. These word representations improved downstream tasks in many domains such as machine translation, syntactic parsing, text classification, and machine comprehension, among other
to list a few example domains.
add a comment |
up vote
1
down vote
Basically anything you might want to do with the results of NLP.
From the intro of one recent article from the arxiv by Christian S. Perone, Roberto Silveira, and Thomas S. Paula:
Word embeddings are nowadays pervasive on a wide spectrum of Natural Language Processing (NLP) and Natural Language Understanding (NLU) applications. These word representations improved downstream tasks in many domains such as machine translation, syntactic parsing, text classification, and machine comprehension, among other
to list a few example domains.
add a comment |
up vote
1
down vote
up vote
1
down vote
Basically anything you might want to do with the results of NLP.
From the intro of one recent article from the arxiv by Christian S. Perone, Roberto Silveira, and Thomas S. Paula:
Word embeddings are nowadays pervasive on a wide spectrum of Natural Language Processing (NLP) and Natural Language Understanding (NLU) applications. These word representations improved downstream tasks in many domains such as machine translation, syntactic parsing, text classification, and machine comprehension, among other
to list a few example domains.
Basically anything you might want to do with the results of NLP.
From the intro of one recent article from the arxiv by Christian S. Perone, Roberto Silveira, and Thomas S. Paula:
Word embeddings are nowadays pervasive on a wide spectrum of Natural Language Processing (NLP) and Natural Language Understanding (NLU) applications. These word representations improved downstream tasks in many domains such as machine translation, syntactic parsing, text classification, and machine comprehension, among other
to list a few example domains.
answered Nov 11 at 12:46
kabanus
10.9k21237
10.9k21237
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