General2Specialized LLMs Translation for E-commerce
Existing Neural Machine Translation (NMT) models mainly handle translation in the general domain, while overlooking domains with special writing formulas, such as e-commerce and legal documents. Taking e-commerce as an example, the texts usually include amounts of domain-related words and have more grammar problems, which leads to inferior performances of current NMT methods. To address these problems, we collect two domain-related resources, including a set of term pairs (aligned Chinese-English bilingual terms) and a parallel corpus annotated for the e-commerce domain. Furthermore, we propose a two-step fine-tuning paradigm (named G2ST) with self-contrastive semantic enhancement to transfer one general NMT model to the specialized NMT model for e-commerce. The paradigm can be used for the NMT models based on Large language models (LLMs). Extensive evaluations on real e-commerce titles demonstrate the superior translation quality and robustness of our G2ST approach, as compared with state-of-the-art NMT models such as LLaMA, Qwen, GPT-3.5, and even GPT-4.
Code (0)
등록된 구현이 없습니다.
Tasks
Machine TranslationNMTTranslationMethods 이 논문이 사용한 방법론
Similar Papers 제목 키워드 기반
Enhancing E-commerce Product Title Translation with Retrieval-Augmented Generation and Large Language Models
E-commerce stores enable multilingual product discovery which require accurate product title translation. Multilingual large language models (LLMs) have shown promising capacity to perform machine translation tasks, and …
Machine TranslationRAGRetrievalRetrieval-augmented Generation+1TransBench: Benchmarking Machine Translation for Industrial-Scale Applications
Machine translation (MT) has become indispensable for cross-border communication in globalized industries like e-commerce, finance, and legal services, with recent advancements in large language models (LLMs) significant…
BenchmarkingMachine TranslationTranslationCompass-v3: Scaling Domain-Specific LLMs for Multilingual E-Commerce in Southeast Asia
Large language models (LLMs) excel in general-domain applications, yet their performance often degrades in specialized tasks requiring domain-specific knowledge. E-commerce is particularly challenging, as its data are no…
Can General-Purpose Large Language Models Generalize to English-Thai Machine Translation ?
Large language models (LLMs) perform well on common tasks but struggle with generalization in low-resource and low-computation settings. We examine this limitation by testing various LLMs and specialized translation mode…
Machine TranslationQuantizationTranslationSurvey of Specialized Large Language Model
The rapid evolution of specialized large language models (LLMs) has transitioned from simple domain adaptation to sophisticated native architectures, marking a paradigm shift in AI development. This survey systematically…
Domain Adaptation