2 citations · 2 across the 4 of their papers we have counts for
4 papers
Towards Effective Disambiguation for Machine Translation with Large Language Models
Vivek Iyer, Pinzhen Chen, Alexandra Birch
Resolving semantic ambiguity has long been recognised as a central challenge in the field of Machine Translation. Recent work on benchmarking translation performance on ambiguous s…
Terminology-Aware Translation with Constrained Decoding and Large Language Model Prompting
Nikolay Bogoychev, Pinzhen Chen
Terminology correctness is important in the downstream application of machine translation, and a prevalent way to ensure this is to inject terminology constraints into a translatio…
Exploring Data Augmentation for Code Generation Tasks
Pinzhen Chen, Gerasimos Lampouras
Advances in natural language processing, such as transfer learning from pre-trained language models, have impacted how models are trained for programming language tasks too. Previo…
To Adapt or to Fine-tune: A Case Study on Abstractive Summarization
Zheng Zhao, Pinzhen Chen
Recent advances in the field of abstractive summarization leverage pre-trained language models rather than train a model from scratch. However, such models are sluggish to train an…