reddit_tifu

  • Description:

Reddit dataset, where TIFU denotes the name of subbreddit /r/tifu. As defined in the publication, styel "short" uses title as summary and "long" uses tldr as summary.

Features includes: - document: post text without tldr. - tldr: tldr line. - title: trimmed title without tldr. - ups: upvotes. - score: score. - num_comments: number of comments. - upvote_ratio: upvote ratio.

FeaturesDict({
    'documents': Text(shape=(), dtype=tf.string),
    'num_comments': tf.float32,
    'score': tf.float32,
    'title': Text(shape=(), dtype=tf.string),
    'tldr': Text(shape=(), dtype=tf.string),
    'ups': tf.float32,
    'upvote_ratio': tf.float32,
})
  • Citation:
@misc{kim2018abstractive,
    title={Abstractive Summarization of Reddit Posts with Multi-level Memory Networks},
    author={Byeongchang Kim and Hyunwoo Kim and Gunhee Kim},
    year={2018},
    eprint={1811.00783},
    archivePrefix={arXiv},
    primaryClass={cs.CL}
}

reddit_tifu/short (default config)

  • Config description: Using title as summary.

  • Splits:

Split Examples
'train' 79,740

reddit_tifu/long

  • Config description: Using TLDR as summary.

  • Splits:

Split Examples
'train' 42,139