266 citations · 1.8k across the 115 of their papers we have counts for
11 papers · 2 filters
A Bayesian Approach for Sequence Tagging with Crowds
Edwin Simpson, Iryna Gurevych
Current methods for sequence tagging, a core task in NLP, are data hungry, which motivates the use of crowdsourcing as a cheap way to obtain labelled data. However, annotators are…
APRIL: Interactively Learning to Summarise by Combining Active Preference Learning and Reinforcement Learning
Yang Gao, Christian M. Meyer, Iryna Gurevych
We propose a method to perform automatic document summarisation without using reference summaries. Instead, our method interactively learns from users' preferences. The merit of pr…
Modeling Semantics with Gated Graph Neural Networks for Knowledge Base Question Answering
Daniil Sorokin, Iryna Gurevych
The most approaches to Knowledge Base Question Answering are based on semantic parsing. In this paper, we address the problem of learning vector representations for complex semanti…
Cross-lingual Argumentation Mining: Machine Translation (and a bit of Projection) is All You Need!
Steffen Eger, Johannes Daxenberger, Christian Stab +1
Argumentation mining (AM) requires the identification of complex discourse structures and has lately been applied with success monolingually. In this work, we show that the existin…
Finding Convincing Arguments Using Scalable Bayesian Preference Learning
Edwin Simpson, Iryna Gurevych
We introduce a scalable Bayesian preference learning method for identifying convincing arguments in the absence of gold-standard rat- ings or rankings. In contrast to previous work…
Multimodal Grounding for Language Processing
Lisa Beinborn, Teresa Botschen, Iryna Gurevych
This survey discusses how recent developments in multimodal processing facilitate conceptual grounding of language. We categorize the information flow in multimodal processing with…