11 citations · 47 across the 16 of their papers we have counts for
17 papers
Trans-Zero: Self-Play Incentivizes Large Language Models for Multilingual Translation Without Parallel Data
Wei Zou, Sen Yang, Yu Bao +3
The rise of Large Language Models (LLMs) has reshaped machine translation (MT), but multilingual MT still relies heavily on parallel data for supervised fine-tuning (SFT), facing c…
MT-PATCHER: Selective and Extendable Knowledge Distillation from Large Language Models for Machine Translation
Jiahuan Li, Shanbo Cheng, Shujian Huang +1
Large Language Models (LLM) have demonstrated their strong ability in the field of machine translation (MT), yet they suffer from high computational cost and latency. Therefore, tr…
Speech Translation with Large Language Models: An Industrial Practice
Zhichao Huang, Rong Ye, Tom Ko +4
Given the great success of large language models (LLMs) across various tasks, in this paper, we introduce LLM-ST, a novel and effective speech translation model constructed upon a…
Only 5\% Attention Is All You Need: Efficient Long-range Document-level Neural Machine Translation
Zihan Liu, Zewei Sun, Shanbo Cheng +2
Document-level Neural Machine Translation (DocNMT) has been proven crucial for handling discourse phenomena by introducing document-level context information. One of the most impor…
BigVideo: A Large-scale Video Subtitle Translation Dataset for Multimodal Machine Translation
Liyan Kang, Luyang Huang, Ningxin Peng +6
We present a large-scale video subtitle translation dataset, BigVideo, to facilitate the study of multi-modality machine translation. Compared with the widely used How2 and VaTeX d…
Visual Information Matters for ASR Error Correction
Vanya Bannihatti Kumar, Shanbo Cheng, Ningxin Peng +1
Aiming to improve the Automatic Speech Recognition (ASR) outputs with a post-processing step, ASR error correction (EC) techniques have been widely developed due to their efficienc…
Better Datastore, Better Translation: Generating Datastores from Pre-Trained Models for Nearest Neural Machine Translation
Jiahuan Li, Shanbo Cheng, Zewei Sun +2
Nearest Neighbor Machine Translation (kNNMT) is a simple and effective method of augmenting neural machine translation (NMT) with a token-level nearest neighbor retrieval mechanism…
Beyond Triplet: Leveraging the Most Data for Multimodal Machine Translation
Yaoming Zhu, Zewei Sun, Shanbo Cheng +3
Multimodal machine translation (MMT) aims to improve translation quality by incorporating information from other modalities, such as vision. Previous MMT systems mainly focus on be…
Controlling Styles in Neural Machine Translation with Activation Prompt
Yifan Wang, Zewei Sun, Shanbo Cheng +2
Controlling styles in neural machine translation (NMT) has attracted wide attention, as it is crucial for enhancing user experience. Earlier studies on this topic typically concent…
Zero-shot Domain Adaptation for Neural Machine Translation with Retrieved Phrase-level Prompts
Zewei Sun, Qingnan Jiang, Shujian Huang +3
Domain adaptation is an important challenge for neural machine translation. However, the traditional fine-tuning solution requires multiple extra training and yields a high cost. I…
Unified Multimodal Punctuation Restoration Framework for Mixed-Modality Corpus
Yaoming Zhu, Liwei Wu, Shanbo Cheng +1
The punctuation restoration task aims to correctly punctuate the output transcriptions of automatic speech recognition systems. Previous punctuation models, either using text only…
The Volctrans GLAT System: Non-autoregressive Translation Meets WMT21
Lihua Qian, Yi Zhou, Zaixiang Zheng +7
This paper describes the Volctrans' submission to the WMT21 news translation shared task for German->English translation. We build a parallel (i.e., non-autoregressive) translation…
Learning Kernel-Smoothed Machine Translation with Retrieved Examples
Qingnan Jiang, Mingxuan Wang, Jun Cao +3
How to effectively adapt neural machine translation (NMT) models according to emerging cases without retraining? Despite the great success of neural machine translation, updating t…
Language Tags Matter for Zero-Shot Neural Machine Translation
Liwei Wu, Shanbo Cheng, Mingxuan Wang +1
Multilingual Neural Machine Translation (MNMT) has aroused widespread interest due to its efficiency. An exciting advantage of MNMT models is that they could also translate between…
AR: Auto-Repair the Synthetic Data for Neural Machine Translation
Shanbo Cheng, Shaohui Kuang, Rongxiang Weng +3
Compared with only using limited authentic parallel data as training corpus, many studies have proved that incorporating synthetic parallel data, which generated by back translatio…
Acquiring Knowledge from Pre-trained Model to Neural Machine Translation
Rongxiang Weng, Heng Yu, Shujian Huang +2
Pre-training and fine-tuning have achieved great success in the natural language process field. The standard paradigm of exploiting them includes two steps: first, pre-training a m…
Improving Multilingual Semantic Textual Similarity with Shared Sentence Encoder for Low-resource Languages
Xin Tang, Shanbo Cheng, Loc Do +5
Measuring the semantic similarity between two sentences (or Semantic Textual Similarity - STS) is fundamental in many NLP applications. Despite the remarkable results in supervised…