This paper presents the results of the General Machine Translation Task organised as part
of the Conference on Machine Translation (WMT) 2022. In the general MT task, participants …

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 …

Knowledge distillation, transferring knowledge from a teacher model to a student model, has
emerged as a powerful technique in neural machine translation for compressing models or …

Applying differential privacy (DP) by means of the DP-SGD algorithm to protect individual
data points during training is becoming increasingly popular in NLP. However, the choice of …

While machine translation (MT) systems are achieving increasingly strong performance on
benchmarks, they often produce translations with errors and anomalies. Understanding …

Automatic metrics for evaluating translation quality are typically validated by measuring how
well they correlate with human assessments. However, correlation methods tend to capture …

Task-oriented conversational datasets often lack topic variability and linguistic diversity.
However, with the advent of Large Language Models (LLMs) pretrained on extensive …

The complexities of chats pose significant challenges for machine translation models.
Recognizing the need for a precise evaluation metric to address the issues of chat …

This study aims to investigate methods for inducing document-level context awareness in
Neural Machine Translation (NMT) models for bilingual chat data. Previous research …