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.
One example is below.
Q: 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?
A: No
Rationale: Based on the context, the dataset is constructed from a famous Chinese social media microblogging service Weibo.
Q: We utilize the VATEX dataset for video captioning, which contains over 41,250 videos and 825,000 captions in both English and Chinese. Among the captions, there are over 206,000 English-Chinese parallel translation pairs. It covers 600 human activities and a variety of video content. Each video is paired with 10 English and 10 Chinese diverse captions. We follow the official split with 25,991 videos for training, 3,000 videos for validation and 6,000 public test videos for final testing.
Question: How big is the dataset used?
A:
over 41,250 videos and 825,000 captions in both English and Chinese. over 206,000 English-Chinese parallel translation pairs