Text Data Encoding Task: Difference between revisions

From GM-RKB
Jump to navigation Jump to search
m (Text replacement - "ments]]" to "ment]]s")
m (Text replacement - "niques]]" to "nique]]s")
 
Line 7: Line 7:
** It can handle various languages and scripts, enabling applications in [[multilingual NLP]].
** It can handle various languages and scripts, enabling applications in [[multilingual NLP]].
** It can leverage [[pretrained language models]] like [[BERT]], [[GPT]], or [[Word2Vec]] for efficient encoding.
** It can leverage [[pretrained language models]] like [[BERT]], [[GPT]], or [[Word2Vec]] for efficient encoding.
** It can improve with advancements in [[neural network architectures]] and [[language modeling techniques]].
** It can improve with advancements in [[neural network architectures]] and [[language modeling technique]]s.
** It can utilize [[contextual embeddings]] to capture the meaning of words based on their usage in sentences.
** It can utilize [[contextual embeddings]] to capture the meaning of words based on their usage in sentences.
** ...
** ...

Latest revision as of 13:40, 21 July 2024

An Text Data Encoding Task is a data encoding task for text data.



References

2018

2013