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.

Input: Consider Input: It is interesting to observe that the baseline model amplifies the bias in the training data set as measured by INLINEFORM0 and INLINEFORM1 . From measurements using the described bias metrics, our method effectively mitigates bias in language modelling without a significant increase in perplexity.
Question: how is mitigation of gender bias evaluated?

Output: Using INLINEFORM0 and INLINEFORM1

Input: Consider Input: To show the effectiveness of our approach, we show results on the SICK dataset BIBREF1, a common benchmark for logic-based NLI, and find MonaLog to be competitive with more complicated logic-based approaches (many of which require full semantic parsing and more complex logical machinery).
Question: Do they beat current state-of-the-art on SICK?

Output: No

Input: Consider Input: We compare our model with two sets of baselines:

MemN2N BIBREF12 is an end-to-end trainable version of memory networks BIBREF9 . Attentive and Impatient Readers BIBREF6 use bidirectional LSTMs to encode question and evidence, and do classification over a large vocabulary based on these two encodings.
Question: What are the baselines?
Output: MemN2N BIBREF12 Attentive and Impatient Readers BIBREF6