activity
20162023
most citedRoot Mean Square Layer Normalization

106 citations · 401 across the 23 of their papers we have counts for

collaborators

44 papers

cs.CL2023

A Benchmark for Evaluating Machine Translation Metrics on Dialects Without Standard Orthography

Noëmi Aepli, Chantal Amrhein, Florian Schottmann +1

For sensible progress in natural language processing, it is important that we are aware of the limitations of the evaluation metrics we use. In this work, we evaluate how robust me…

cs.CL2022

As Little as Possible, as Much as Necessary: Detecting Over- and Undertranslations with Contrastive Conditioning

Jannis Vamvas, Rico Sennrich

Omission and addition of content is a typical issue in neural machine translation. We propose a method for detecting such phenomena with off-the-shelf translation models. Using con…

cs.CL2021

On the Limits of Minimal Pairs in Contrastive Evaluation

Jannis Vamvas, Rico Sennrich

Minimal sentence pairs are frequently used to analyze the behavior of language models. It is often assumed that model behavior on contrastive pairs is predictive of model behavior…

cs.CL2021

Vision Matters When It Should: Sanity Checking Multimodal Machine Translation Models

Jiaoda Li, Duygu Ataman, Rico Sennrich

Multimodal machine translation (MMT) systems have been shown to outperform their text-only neural machine translation (NMT) counterparts when visual context is available. However,…

cs.CL2021

Language Modeling, Lexical Translation, Reordering: The Training Process of NMT through the Lens of Classical SMT

Elena Voita, Rico Sennrich, Ivan Titov

Differently from the traditional statistical MT that decomposes the translation task into distinct separately learned components, neural machine translation uses a single neural ne…

cs.CL2021

How Suitable Are Subword Segmentation Strategies for Translating Non-Concatenative Morphology?

Chantal Amrhein, Rico Sennrich

Data-driven subword segmentation has become the default strategy for open-vocabulary machine translation and other NLP tasks, but may not be sufficiently generic for optimal learni…