A metaverse: Taxonomy, components, applications, and open challenges
SM Park, YG Kim - IEEE access, 2022 - ieeexplore.ieee.org
Unlike previous studies on the Metaverse based on Second Life, the current Metaverse is
based on the social value of Generation Z that online and offline selves are not different …
based on the social value of Generation Z that online and offline selves are not different …
The Eval4NLP shared task on explainable quality estimation: Overview and results
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 …
estimation. Given a source-translation pair, this shared task requires not only to provide a …
Improving translation quality estimation with bias mitigation
State-of-the-art translation Quality Estimation (QE) models are proven to be biased. More
specifically, they over-rely on monolingual features while ignoring the bilingual semantic …
specifically, they over-rely on monolingual features while ignoring the bilingual semantic …
As little as possible, as much as necessary: Detecting over-and undertranslations with contrastive conditioning
J Vamvas, R Sennrich - arXiv preprint arXiv:2203.01927, 2022 - arxiv.org
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 …
propose a method for detecting such phenomena with off-the-shelf translation models. Using …
Multi-view fusion for universal translation quality estimation
Abstract Machine translation quality estimation (QE) aims to evaluate the result of translation
without reference. Despite the progress it has made, state-of-the-art QE models are proven …
without reference. Despite the progress it has made, state-of-the-art QE models are proven …
Not all errors are equal: Learning text generation metrics using stratified error synthesis
Is it possible to build a general and automatic natural language generation (NLG) evaluation
metric? Existing learned metrics either perform unsatisfactorily or are restricted to tasks …
metric? Existing learned metrics either perform unsatisfactorily or are restricted to tasks …
Translation error detection as rationale extraction
Recent Quality Estimation (QE) models based on multilingual pre-trained representations
have achieved very competitive results when predicting the overall quality of translated …
have achieved very competitive results when predicting the overall quality of translated …
Self-supervised quality estimation for machine translation
Quality estimation (QE) of machine translation (MT) aims to evaluate the quality of machine-
translated sentences without references and is important in practical applications of MT …
translated sentences without references and is important in practical applications of MT …
Improved pseudo data for machine translation quality estimation with constrained beam search
Abstract Machine translation (MT) quality estimation (QE) is a crucial task to estimate the
quality of MT outputs when reference translations are unavailable. Many studies focus on …
quality of MT outputs when reference translations are unavailable. Many studies focus on …
Mismatching-aware unsupervised translation quality estimation for low-resource languages
Abstract Translation Quality Estimation (QE) is the task of predicting the quality of machine
translation (MT) output without any reference. This task has gained increasing attention as …
translation (MT) output without any reference. This task has gained increasing attention as …