266 citations · 282 across the 6 of their papers we have counts for
7 papers
Classification and Clustering of Arguments with Contextualized Word Embeddings
Nils Reimers, Benjamin Schiller, Tilman Beck +3
We experiment with two recent contextualized word embedding methods (ELMo and BERT) in the context of open-domain argument search. For the first time, we show how to leverage the p…
Preference-based Interactive Multi-Document Summarisation
Yang Gao, Christian M. Meyer, Iryna Gurevych
Interactive NLP is a promising paradigm to close the gap between automatic NLP systems and the human upper bound. Preference-based interactive learning has been successfully applie…
Analysis of Automatic Annotation Suggestions for Hard Discourse-Level Tasks in Expert Domains
Claudia Schulz, Christian M. Meyer, Jan Kiesewetter +5
Many complex discourse-level tasks can aid domain experts in their work but require costly expert annotations for data creation. To speed up and ease annotations, we investigate th…
Pitfalls in the Evaluation of Sentence Embeddings
Steffen Eger, Andreas Rücklé, Iryna Gurevych
Deep learning models continuously break new records across different NLP tasks. At the same time, their success exposes weaknesses of model evaluation. Here, we compile several key…
Lexical-semantic resources: yet powerful resources for automatic personality classification
Xuan-Son Vu, Lucie Flekova, Lili Jiang +1
In this paper, we aim to reveal the impact of lexical-semantic resources, used in particular for word sense disambiguation and sense-level semantic categorization, on automatic per…
Optimal Hyperparameters for Deep LSTM-Networks for Sequence Labeling Tasks
Nils Reimers, Iryna Gurevych
Selecting optimal parameters for a neural network architecture can often make the difference between mediocre and state-of-the-art performance. However, little is published which p…