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.

[Q]: As fig:fit shows, estimated test accuracy is highly correlated with actual test accuracy for various datasets, with worst-case values $\mu <1\%$ and $\sigma <5\%$ . Note that the number of free parameters is small ($||\le 6$) compared to the number of points (42–49 model-data configurations), demonstrating the appropriateness of the proposed function for modeling the complex error landscape. 
 Question: What is proof that proposed functional form approximates well generalization error in practice?
[A]: estimated test accuracy is highly correlated with actual test accuracy for various datasets appropriateness of the proposed function for modeling the complex error landscape


[Q]: Embedding: We developed different variations of our models with a simple lookup table embeddings learned from scratch and using high-performance contextual embeddings, which are ELMo BIBREF11, BERT BIBREF16 and ClinicalBERT BIBREF13 (trained and provided by the authors). 
 Question: What embeddings are used?
[A]:  simple lookup table embeddings learned from scratch using high-performance contextual embeddings, which are ELMo BIBREF11, BERT BIBREF16 and ClinicalBERT BIBREF13


[Q]: We used two parallel corpora: Asian Scientific Paper Excerpt Corpus (ASPEC) BIBREF0 and NTCIR PatentMT Parallel Corpus BIBREF1 . 
 Question: What parallel corpus did they use?
[A]:
Asian Scientific Paper Excerpt Corpus (ASPEC) BIBREF0 NTCIR PatentMT Parallel Corpus BIBREF1