Papers by Carsten Binnig

2 papers
Know Better – A Clickbait Resolving Challenge (2022.lrec-1)

Copied to clipboard

Challenge: a clickbait headline or teaser is used to "bait" the reader into clicking a link to an article . clickbaiting is annoying but effective, and can be countered with specialized models .
Approach: They propose to construct approaches that can automatically extract relevant information from clickbait articles . they argue that clickbaiting can probably not be defeated with clickbaitting detection alone .
Outcome: The proposed methods outperform question answering models on clickbait resolving task . the data will be used to give users tools to counter clickbaiting in the future .
Summarization Beyond News: The Automatically Acquired Fandom Corpora (2020.lrec-1)

Copied to clipboard

Challenge: Abstractive summarization methods require large corpora to train neural architectures.
Approach: They propose a novel automatic corpus construction approach that automatically constructs large open-licensed summarization corpora from existing large text collections and an evaluation process with human annotators.
Outcome: The proposed approach can be used to train abstractive summarization models on large corpora and through a manual evaluation with human annotators.

What is GenGO?

GenGO is an NLP powered publication search system. It currenctly indexes 30k+ papers from ACL Anthology, and implements multi-aspect summarization, semantic search, and more!

Information

About
Limitations