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Found 6 papers, 1 papers with code
Incorporating External Annotation to improve Named Entity Translation in NMT
The correct translation of named entities (NEs) still poses a challenge for conventional neural machine translation (NMT) systems.
Terminology-Constrained Neural Machine Translation at SAP
This paper examines approaches to bias a neural machine translation model to adhere to terminology constraints in an industrial setup.
“Hi, how can I help you?” Improving Machine Translation of Conversational Content in a Business Context
This paper addresses the automatic translation of conversational content in a business context, for example support chat dialogues.
Contextual Refinement of Translations: Large Language Models for Sentence and Document-Level Post-Editing
Building on the LLM's exceptional ability to process and generate lengthy sequences, we also propose extending our approach to document-level translation.
Enhancing Supervised Learning with Contrastive Markings in Neural Machine Translation Training
Supervised learning in Neural Machine Translation (NMT) typically follows a teacher forcing paradigm where reference tokens constitute the conditioning context in the model's prediction, instead of its own previous predictions.
A Parallel Evaluation Data Set of Software Documentation with Document Structure Annotation
This paper accompanies the software documentation data set for machine translation, a parallel evaluation data set of data originating from the SAP Help Portal, that we released to the machine translation community for research purposes.
