Anchoring the Judge: Curriculum-Based Adaptation and Reference-Anchored MQM for LLM-Based Machine Translation of an Unseen Low-Resource Language - A Case of Nupe

Domain:

natural language processing

Creator:

UmaSulABD

Publisher:

Ass

Host:

Visit

doi.org

Tasks

machine translation

LLM-Based Evaluation of Low-Resource Machine Translation: A Reference-less Dialect Guided Approach with a Refined Sylheti-English Benchmark

Evaluating machine translation (MT) for low-resource languages poses a persistent challenge, primari

Low-Resource Machine Translation Training Curriculum Fit for Low-Resource Languages

We conduct an empirical study of neural machine translation (NMT) for truly low-resource languages,

Simultaneous Machine Translation using LLM on LRL (low-resource language)

Simultaneous machine translation (SiMT) allows the real-time communication, regardless of language,

Typologically-Informed Candidate Reranking for LLM-based Translation into Low-Resource Languages

Large language models trained predominantly on high-resource languages exhibit systematic biases tow

Crowdsourced Phrase-Based Tokenization for Low-Resourced Neural Machine Translation: The Case of Fon Language

Building effective neural machine translation (NMT) models for very low-resourced and morphologically rich African indigenous languages is an open challenge. Besides the issue of finding available resources for them, a lot of work is put into preprocessing and toke

A comparison of pipelines for the translation of a low resource language based on transformers

This work compares three pipelines for training transformer-based neural networks to produce machine