Recent work has shown evidence of 'Clever Hans' behavior in high-perform...
Despite recent advancements in speech recognition, there are still
diffi...
Existing approaches for unsupervised bilingual lexicon induction (BLI) o...
Dense vector representations for textual data are crucial in modern NLP....
Document-level neural machine translation (NMT) has outperformed
sentenc...
Hybrid tabular-textual question answering (QA) requires reasoning from
h...
Recent work has shown that neural feature- and representation-learning, ...
Recent research on style transfer takes inspiration from unsupervised ne...
Cross-lingual natural language processing relies on translation, either ...
Traditional hand-crafted linguistically-informed features have often bee...
For most language combinations, parallel data is either scarce or simply...
Inflection is an essential part of every human language's morphology, ye...
Increasing the depth of models allows neural models to model complicated...
The Transformer translation model (Vaswani et al., 2017) based on a
mult...
The choice of hyper-parameters affects the performance of neural models....
Self-supervised neural machine translation (SS-NMT) learns how to
extrac...
Multilingualism is a cultural cornerstone of Europe and firmly anchored ...
The Transformer translation model is popular for its effective
paralleli...
The Transformer translation model employs residual connection and layer
...
We analyse coreference phenomena in three neural machine translation sys...
In automatic post-editing (APE) it makes sense to condition post-editing...
This paper describes strategies to improve an existing web-based
compute...
In this paper we present the UDS-DFKI system submitted to the Similar
La...
In this paper, we describe our submission to the English-German APE shar...
Current advances in machine translation increase the need for translator...
The advent of representation learning methods enabled large performance ...
In this paper, we investigate the application of text classification met...
In this paper, we investigate the application of text classification met...
Grapheme-to-phoneme conversion (g2p) is necessary for text-to-speech and...
End-to-end neural machine translation has overtaken statistical machine
...
This paper investigates the robustness of NLP against perturbed word for...
This paper investigates neural character-based morphological tagging for...