158 citations · 240 across the 9 of their papers we have counts for
9 papers
Efficient Multi-Task Scene Analysis with RGB-D Transformers
Söhnke Benedikt Fischedick, Daniel Seichter, Robin Schmidt +2
Scene analysis is essential for enabling autonomous systems, such as mobile robots, to operate in real-world environments. However, obtaining a comprehensive understanding of the s…
Learning Language-Specific Layers for Multilingual Machine Translation
Telmo Pessoa Pires, Robin M. Schmidt, Yi-Hsiu Liao +1
Multilingual Machine Translation promises to improve translation quality between non-English languages. This is advantageous for several reasons, namely lower latency (no need to t…
State Spaces Aren't Enough: Machine Translation Needs Attention
Ali Vardasbi, Telmo Pessoa Pires, Robin M. Schmidt +1
Structured State Spaces for Sequences (S4) is a recently proposed sequence model with successful applications in various tasks, e.g. vision, language modeling, and audio. Thanks to…
Non-Autoregressive Neural Machine Translation: A Call for Clarity
Robin M. Schmidt, Telmo Pires, Stephan Peitz +1
Non-autoregressive approaches aim to improve the inference speed of translation models by only requiring a single forward pass to generate the output sequence instead of iterativel…
NL-Augmenter: A Framework for Task-Sensitive Natural Language Augmentation
Kaustubh D. Dhole, Varun Gangal, Sebastian Gehrmann +122
Data augmentation is an important component in the robustness evaluation of models in natural language processing (NLP) and in enhancing the diversity of the data they are trained…
Explainability-aided Domain Generalization for Image Classification
Robin M. Schmidt
Traditionally, for most machine learning settings, gaining some degree of explainability that tries to give users more insights into how and why the network arrives at its predicti…