From b04b38354b3245fb543c72ae2b2baa2bf571bef7 Mon Sep 17 00:00:00 2001 From: Daisy Deng Date: Thu, 16 Apr 2020 18:59:10 +0000 Subject: [PATCH] update documentation --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index 64e36f0..d436397 100755 --- a/README.md +++ b/README.md @@ -50,7 +50,7 @@ The following is a summary of the commonly used NLP scenarios covered in the rep |-------------------------| ------------------- |-------|---| |Text Classification |BERT, XLNet, RoBERTa| Text classification is a supervised learning method of learning and predicting the category or the class of a document given its text content. |English, Hindi, Arabic| |Named Entity Recognition |BERT| Named entity recognition (NER) is the task of classifying words or key phrases of a text into predefined entities of interest. |English| -|Text Summarization|BERTSumExt
BERTSumAbs
UniLM (s2s-ft)|Text summarization is a language generation task of summarizing the input text into a shorter paragraph of text.|English +|Text Summarization|BERTSumExt
BERTSumAbs
UniLM (s2s-ft)
MiniLM |Text summarization is a language generation task of summarizing the input text into a shorter paragraph of text.|English |Entailment |BERT, XLNet, RoBERTa| Textual entailment is the task of classifying the binary relation between two natural-language texts, *text* and *hypothesis*, to determine if the *text* agrees with the *hypothesis* or not. |English| |Question Answering |BiDAF, BERT, XLNet| Question answering (QA) is the task of retrieving or generating a valid answer for a given query in natural language, provided with a passage related to the query. |English| |Sentence Similarity |BERT, GenSen| Sentence similarity is the process of computing a similarity score given a pair of text documents. |English|