2404.02835
arxiv.org · 144 words · saved by 1 readers
N/A
Retrieving Examples from Memory for Retrieval Augmented Neural Machine Translation: A Systematic Comparison Retrieval-Augmented Neural Machine Translation (RAMT) architectures retrieve examples from memory to guide the generation process. While most works in this trend explore new ways to exploit the retrieved examples, the upstream retrieval step is mostly unexplored. In this paper, we study the effect of varying retrieval methods for several translation architectures, to better understand the interplay between these two processes. We conduct experiments in two language pairs in a multi-doma
saved by
related reading
- 2025.findings-emnlp.313.pdfaclanthology.org
- Exploring In-context Example Generation for Machine Translationaclanthology.org
- 2025.acl-long.429.pdfaclanthology.org
- Multi-perspective Alignment for Increasing Naturalness in Neural Machine Translation - ACL Anthologyaclanthology.org
- 2025.acl-srw.17.pdfaclanthology.org
- DRT: Deep Reasoning Translation via Long Chain-of-Thought - ACL Anthologyaclanthology.org
- Reasoning for Translation: Comparative Analysis of Chain-of-Thought and Tree-of-Thought Prompting for LLM Translation - ACL Anthologyaclanthology.org
- Neural Machine Translation for Agglutinative Languages via Data Rejuvenation - ACL Anthologyaclanthology.org
- 2024.emnlp-main.914.pdfaclanthology.org
- LLM-based Translation Inference with Iterative Bilingual Understandingaclanthology.org
- Understanding In-Context Machine Translation for Low-Resource Languages: A Case Study on Manchu - ACL Anthologyaclanthology.org
- Enhancing Human Evaluation in Machine Translation with Comparative Judgement - ACL Anthologyaclanthology.org