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Exploiting Personal Characteristics of Debaters for Predicting Persuasiveness
Predicting the persuasiveness of arguments has applications as diverse as writing assistance, essay scoring, and advertising.
Towards Summarization for Social Media - Results of the TL;DR Challenge
In this paper, we report on the results of the TL;DR challenge, discussing an extensive manual evaluation of the expected properties of a good summary based on analyzing the comments provided by human annotators.
Task Proposal: The TL;DR Challenge
The TL;DR challenge fosters research in abstractive summarization of informal text, the largest and fastest-growing source of textual data on the web, which has been overlooked by summarization research so far.
TL;DR: Mining Reddit to Learn Automatic Summarization
Recent advances in automatic text summarization have used deep neural networks to generate high-quality abstractive summaries, but the performance of these models strongly depends on large amounts of suitable training data.
