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 …

Large language models (LLMs) have significantly advanced various natural language
processing (NLP) tasks. Recent research indicates that moderately-sized LLMs often …

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 …

Recently, there has been a growing interest in designing text generation systems from a
discourse coherence perspective, eg, modeling the interdependence between sentences …

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 …

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 …

Resolving ambiguities through interaction is a hallmark of natural language, and modeling
this behavior is a core challenge in crafting AI assistants. In this work, we study such …

We hypothesize that existing sentence-level machine translation (MT) metrics become less
effective when the human reference contains ambiguities. To verify this hypothesis, we …

Gender inclusivity in language technologies has become a prominent research topic. In this
study, we explore gender-neutral translation (GNT) as a form of gender inclusivity and a goal …

Although proper handling of discourse significantly contributes to the quality of machine
translation (MT), these improvements are not adequately measured in common translation …