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.

Example input: We evaluate the proposed approach on the Chinese social media text summarization task, based on the sequence-to-sequence model. Large-Scale Chinese Short Text Summarization Dataset (LCSTS) is constructed by BIBREF1 . The dataset consists of more than 2.4 million text-summary pairs in total, constructed from a famous Chinese social media microblogging service Weibo.
Question: Are results reported only for English data?
Example output: No
Example explanation: Based on the context, the dataset is constructed from a famous Chinese social media microblogging service Weibo.
Q: We follow a similar evaluation protocol to those presented in BIBREF6 , BIBREF8 , BIBREF9 which is to use our learned representations as features for a low complexity classifier (typically linear) on a novel supervised task/domain unseen during training without updating the parameters of our sentence representation model. We also consider such a transfer learning evaluation in an artificially constructed low-resource setting. In addition, we also evaluate the quality of our learned individual word representations using standard benchmarks BIBREF36 , BIBREF37 .
Question: How do they evaluate their sentence representations?
A:
standard benchmarks BIBREF36 , BIBREF37 to use our learned representations as features for a low complexity classifier (typically linear) on a novel supervised task/domain unseen during training without updating the parameters transfer learning evaluation in an artificially constructed low-resource setting