Given the task definition, example input & output, solve the new input case.
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: 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?
Output: No
Based on the context, the dataset is constructed from a famous Chinese social media microblogging service Weibo.

New input case for you: Machine translation finds use in cheminformatics in "translation" from one language (e.g. reactants) to another (e.g. products). The variational Auto-encoder (VAE) is another widely adopted text generation architecture BIBREF101. Generative Adversarial Network (GAN) models generate novel molecules by using two components: the generator network generates novel molecules, and the discriminator network aims to distinguish between the generated molecules and real molecules BIBREF107.
Question: Are this models usually semi/supervised or unsupervised?
Output:
Both supervised and unsupervised, depending on the task that needs to be solved.