The ready availability of machine translation (MT) systems such as Google Translate has
profoundly changed how society engages with multilingual communication practices. In …

We present the joint contribution of IST and Unbabel to the WMT 2022 Shared Task on
Quality Estimation (QE). Our team participated on all three subtasks:(i) Sentence and Word …

In this paper, we introduce the Eval4NLP-2021shared task on explainable quality
estimation. Given a source-translation pair, this shared task requires not only to provide a …

Sentence Simplification (SS) aims to modify a sentence in order to make it easier to read
and understand. In order to do so, several rewriting transformations can be performed such …

We introduce OpenKiwi, a PyTorch-based open source framework for translation quality
estimation. OpenKiwi supports training and testing of word-level and sentence-level quality …

Assessing the quality of natural language generation (NLG) systems through human
annotation is very expensive. Additionally, human annotation campaigns are time …

Beam search is the go-to method for decoding auto-regressive machine translation models.
While it yields consistent improvements in terms of BLEU, it is only concerned with finding …

We present the joint contribution of Unbabel and Instituto Superior T\'ecnico to the WMT
2023 Shared Task on Quality Estimation (QE). Our team participated on all tasks: sentence …

While several studies report translator resistance to post-editing, translators whose work has
followed the evolution of translation technology may consider post-editing to be translation …

We present MLQE-PE, a new dataset for Machine Translation (MT) Quality Estimation (QE)
and Automatic Post-Editing (APE). The dataset contains eleven language pairs, with human …