85 citations · 533 across the 53 of their papers we have counts for
9 papers · 1 filter
Semantic Change and Emerging Tropes In a Large Corpus of New High German Poetry
Thomas Haider, Steffen Eger
Due to its semantic succinctness and novelty of expression, poetry is a great test bed for semantic change analysis. However, so far there is a scarcity of large diachronic corpora…
MoverScore: Text Generation Evaluating with Contextualized Embeddings and Earth Mover Distance
Wei Zhao, Maxime Peyrard, Fei Liu +3
A robust evaluation metric has a profound impact on the development of text generation systems. A desirable metric compares system output against references based on their semantic…
DBPal: Weak Supervision for Learning a Natural Language Interface to Databases
Nathaniel Weir, Andrew Crotty, Alex Galakatos +9
This paper describes DBPal, a new system to translate natural language utterances into SQL statements using a neural machine translation model. While other recent approaches use ne…
Towards Scalable and Reliable Capsule Networks for Challenging NLP Applications
Wei Zhao, Haiyun Peng, Steffen Eger +2
Obstacles hindering the development of capsule networks for challenging NLP applications include poor scalability to large output spaces and less reliable routing processes. In thi…
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…
Does My Rebuttal Matter? Insights from a Major NLP Conference
Yang Gao, Steffen Eger, Ilia Kuznetsov +2
Peer review is a core element of the scientific process, particularly in conference-centered fields such as ML and NLP. However, only few studies have evaluated its properties empi…
Predicting Research Trends From Arxiv
Steffen Eger, Chao Li, Florian Netzer +1
We perform trend detection on two datasets of Arxiv papers, derived from its machine learning (cs.LG) and natural language processing (cs.CL) categories. Our approach is bottom-up:…
Text Processing Like Humans Do: Visually Attacking and Shielding NLP Systems
Steffen Eger, Gözde Gül Şahin, Andreas Rücklé +6
Visual modifications to text are often used to obfuscate offensive comments in social media (e.g., "!d10t") or as a writing style ("1337" in "leet speak"), among other scenarios. W…
Is it Time to Swish? Comparing Deep Learning Activation Functions Across NLP tasks
Steffen Eger, Paul Youssef, Iryna Gurevych
Activation functions play a crucial role in neural networks because they are the nonlinearities which have been attributed to the success story of deep learning. One of the current…