Large language models effectively leverage document-level context for literary translation, but critical errors persist
M Karpinska, M Iyyer - arXiv preprint arXiv:2304.03245, 2023 - arxiv.org
Large language models (LLMs) are competitive with the state of the art on a wide range of
sentence-level translation datasets. However, their ability to translate paragraphs and …
sentence-level translation datasets. However, their ability to translate paragraphs and …
A survey on zero pronoun translation
Zero pronouns (ZPs) are frequently omitted in pro-drop languages (eg Chinese, Hungarian,
and Hindi), but should be recalled in non-pro-drop languages (eg English). This …
and Hindi), but should be recalled in non-pro-drop languages (eg English). This …
Discoscore: Evaluating text generation with bert and discourse coherence
Recently, there has been a growing interest in designing text generation systems from a
discourse coherence perspective, eg, modeling the interdependence between sentences …
discourse coherence perspective, eg, modeling the interdependence between sentences …
Measuring and increasing context usage in context-aware machine translation
Recent work in neural machine translation has demonstrated both the necessity and
feasibility of using inter-sentential context--context from sentences other than those currently …
feasibility of using inter-sentential context--context from sentences other than those currently …
Investigating the translation performance of a large multilingual language model: the case of bloom
The NLP community recently saw the release of a new large open-access multilingual
language model, BLOOM (BigScience et al., 2022) covering 46 languages. We focus on …
language model, BLOOM (BigScience et al., 2022) covering 46 languages. We focus on …
Do context-aware translation models pay the right attention?
Context-aware machine translation models are designed to leverage contextual information,
but often fail to do so. As a result, they inaccurately disambiguate pronouns and polysemous …
but often fail to do so. As a result, they inaccurately disambiguate pronouns and polysemous …
Findings of the WMT 2020 shared task on chat translation
We report the results of the first edition of the WMT shared task on chat translation. The task
consisted of translating bilingual conversational text, in particular customer support chats for …
consisted of translating bilingual conversational text, in particular customer support chats for …
Embarrassingly easy document-level MT metrics: How to convert any pretrained metric into a document-level metric
We hypothesize that existing sentence-level machine translation (MT) metrics become less
effective when the human reference contains ambiguities. To verify this hypothesis, we …
effective when the human reference contains ambiguities. To verify this hypothesis, we …
Quantifying the plausibility of context reliance in neural machine translation
Establishing whether language models can use contextual information in a human-plausible
way is important to ensure their safe adoption in real-world settings. However, the questions …
way is important to ensure their safe adoption in real-world settings. However, the questions …
Document-level language models for machine translation
Despite the known limitations, most machine translation systems today still operate on the
sentence-level. One reason for this is, that most parallel training data is only sentence-level …
sentence-level. One reason for this is, that most parallel training data is only sentence-level …