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.

[EX Q]: Our model contains five independent decoders, one for each image in the sequence. This allows each decoder to learn a specific language model for each position of the sequence. 
 Question: Do the decoder LSTMs all have the same weights?
[EX A]: No

[EX Q]: Based on the gained insights, we have improved the state-of-the-art in XNLI for the Translate-Test and Zero-Shot approaches by a substantial margin. 
 Question: Is the improvement over state-of-the-art statistically significant?
[EX A]: Yes

[EX Q]: We use Waseem and Hovy BIBREF5, Davidson et al. BIBREF9, and Waseem et al. BIBREF10 as baselines and compare the results with our different fine-tuning strategies using pre-trained BERTbase model.  
 Question: What existing approaches do they compare to?
[EX A]:
Waseem and Hovy BIBREF5, Davidson et al. BIBREF9, and Waseem et al. BIBREF10