In this task, you will be presented with a context from an academic paper and a question separated with a 
. You have to answer the question based on the context.
--------
Question: Twitter data: We used the Twitter API to scrap tweets with hashtags. All non-English tweets were filtered out by the API. 
 Question: Do they evaluate only on English datasets?

Answer: Yes


Question: In this work, we develop a technique to rapidly transfer an existing pre-trained model from English to other languages in an energy efficient way BIBREF8.  
 Question: How much training data from the non-English language is used by the system?

Answer: No data. Pretrained model is used.


Question: $LS \cup KLD \cup CONN$ and $KLD \cup LS \cup LS_{inter}$ are the best systems with the highest recall and F1-score respectively. 
 Question: What was previous state-of-the-art approach?

Answer:
TextCNN, TextRNN, SASE, DPCNN, and BERT $LS \cup KLD \cup CONN$ and $KLD \cup LS \cup LS_{inter}$ are the best systems with the highest recall and F1-score respectively