activity
20192024
most citedXFORMAL: A Benchmark for Multilingual Formality Style Transfer

1 citations · 1 across the 7 of their papers we have counts for

collaborators

9 papers

cs.CL2024

On the Implications of Verbose LLM Outputs: A Case Study in Translation Evaluation

Eleftheria Briakou, Zhongtao Liu, Colin Cherry +1

This paper investigates the impact of verbose LLM translations on evaluation. We first demonstrate the prevalence of this behavior across several LLM outputs drawn from the WMT 202…

cs.CL2024

Translating Step-by-Step: Decomposing the Translation Process for Improved Translation Quality of Long-Form Texts

Eleftheria Briakou, Jiaming Luo, Colin Cherry +1

In this paper we present a step-by-step approach to long-form text translation, drawing on established processes in translation studies. Instead of viewing machine translation as a…

cs.CL2022

Can Synthetic Translations Improve Bitext Quality?

Eleftheria Briakou, Marine Carpuat

Synthetic translations have been used for a wide range of NLP tasks primarily as a means of data augmentation. This work explores, instead, how synthetic translations can be used t…

cs.CL2021

Evaluating the Evaluation Metrics for Style Transfer: A Case Study in Multilingual Formality Transfer

Eleftheria Briakou, Sweta Agrawal, Joel Tetreault +1

While the field of style transfer (ST) has been growing rapidly, it has been hampered by a lack of standardized practices for automatic evaluation. In this paper, we evaluate leadi…

cs.CL2021

A Review of Human Evaluation for Style Transfer

Eleftheria Briakou, Sweta Agrawal, Ke Zhang +2

This paper reviews and summarizes human evaluation practices described in 97 style transfer papers with respect to three main evaluation aspects: style transfer, meaning preservati…

cs.CL2021

Beyond Noise: Mitigating the Impact of Fine-grained Semantic Divergences on Neural Machine Translation

Eleftheria Briakou, Marine Carpuat

While it has been shown that Neural Machine Translation (NMT) is highly sensitive to noisy parallel training samples, prior work treats all types of mismatches between source and t…