Contrastive preference optimization: Pushing the boundaries of llm performance in machine translation
Moderate-sized large language models (LLMs)--those with 7B or 13B parameters--exhibit
promising machine translation (MT) performance. However, even the top-performing 13B …
promising machine translation (MT) performance. However, even the top-performing 13B …
xTower: A multilingual LLM for explaining and correcting translation errors
While machine translation (MT) systems are achieving increasingly strong performance on
benchmarks, they often produce translations with errors and anomalies. Understanding …
benchmarks, they often produce translations with errors and anomalies. Understanding …
Findings of the Quality Estimation Shared Task at WMT 2024 Are LLMs Closing the Gap in QE?
We report the results of the WMT 2024 shared task on Quality Estimation, in which the
challenge is to predict the quality of the output of neural machine translation systems at the …
challenge is to predict the quality of the output of neural machine translation systems at the …
X-alma: Plug & play modules and adaptive rejection for quality translation at scale
Large language models (LLMs) have achieved remarkable success across various NLP
tasks, yet their focus has predominantly been on English due to English-centric pre-training …
tasks, yet their focus has predominantly been on English due to English-centric pre-training …
MQM-APE: Toward High-Quality Error Annotation Predictors with Automatic Post-Editing in LLM Translation Evaluators
Large Language Models (LLMs) have shown significant potential as judges for Machine
Translation (MT) quality assessment, providing both scores and fine-grained feedback …
Translation (MT) quality assessment, providing both scores and fine-grained feedback …
Guardians of the Machine Translation Meta-Evaluation: Sentinel Metrics Fall In!
Annually, at the Conference of Machine Translation (WMT), the Metrics Shared Task
organizers conduct the meta-evaluation of Machine Translation (MT) metrics, ranking them …
organizers conduct the meta-evaluation of Machine Translation (MT) metrics, ranking them …
Graph representations for machine translation in dialogue settings
L Krause, SB Santamaria, JC Kalo - Proceedings of the Ninth …, 2024 - aclanthology.org
In this paper, we present our approach to the WMT24-Chat Task, addressing the challenge
of translating chat conversations. Chat conversations are characterised by their informal …
of translating chat conversations. Chat conversations are characterised by their informal …
Can LLMs Really Learn to Translate a Low-Resource Language from One Grammar Book?
Extremely low-resource (XLR) languages lack substantial corpora for training NLP models,
motivating the use of all available resources such as dictionaries and grammar books …
motivating the use of all available resources such as dictionaries and grammar books …
QUEST: Quality-Aware Metropolis-Hastings Sampling for Machine Translation
An important challenge in machine translation (MT) is to generate high-quality and diverse
translations. Prior work has shown that the estimated likelihood from the MT model …
translations. Prior work has shown that the estimated likelihood from the MT model …
Modeling User Preferences with Automatic Metrics: Creating a High-Quality Preference Dataset for Machine Translation
Alignment with human preferences is an important step in developing accurate and safe
large language models. This is no exception in machine translation (MT), where better …
large language models. This is no exception in machine translation (MT), where better …