2 citations · 4 across the 18 of their papers we have counts for
18 papers
Align-then-Slide: A complete evaluation framework for Ultra-Long Document-Level Machine Translation
Jiaxin Guo, Daimeng Wei, Yuanchang Luo +8
Large language models (LLMs) have ushered in a new era for document-level machine translation (\textit{doc}-mt), yet their whole-document outputs challenge existing evaluation meth…
Generative Annotation for ASR Named Entity Correction
Yuanchang Luo, Daimeng Wei, Shaojun Li +8
End-to-end automatic speech recognition systems often fail to transcribe domain-specific named entities, causing catastrophic failures in downstream tasks. Numerous fast and lightw…
Combining the Best of Both Worlds: A Method for Hybrid NMT and LLM Translation
Zhanglin Wu, Daimeng Wei, Xiaoyu Chen +7
Large language model (LLM) shows promising performances in a variety of downstream tasks, such as machine translation (MT). However, using LLMs for translation suffers from high co…
Automatic Evaluation Metrics for Document-level Translation: Overview, Challenges and Trends
Jiaxin GUO, Xiaoyu Chen, Zhiqiang Rao +5
With the rapid development of deep learning technologies, the field of machine translation has witnessed significant progress, especially with the advent of large language models (…
Chain-of-Description: What I can understand, I can put into words
Jiaxin Guo, Daimeng Wei, Zongyao Li +3
In this paper, we propose a novel strategy defined as Chain-of-Description (CoD) Prompting, tailored for Multi-Modal Large Language Models. This approach involves having the model…
Doc-Guided Sent2Sent++: A Sent2Sent++ Agent with Doc-Guided memory for Document-level Machine Translation
Jiaxin Guo, Yuanchang Luo, Daimeng Wei +8
The field of artificial intelligence has witnessed significant advancements in natural language processing, largely attributed to the capabilities of Large Language Models (LLMs).…
M-Ped: Multi-Prompt Ensemble Decoding for Large Language Models
Jiaxin Guo, Daimeng Wei, Yuanchang Luo +8
With the widespread application of Large Language Models (LLMs) in the field of Natural Language Processing (NLP), enhancing their performance has become a research hotspot. This p…
HW-TSC's Submission to the CCMT 2024 Machine Translation Tasks
Zhanglin Wu, Yuanchang Luo, Daimeng Wei +9
This paper presents the submission of Huawei Translation Services Center (HW-TSC) to machine translation tasks of the 20th China Conference on Machine Translation (CCMT 2024). We p…
Context-aware and Style-related Incremental Decoding framework for Discourse-Level Literary Translation
Yuanchang Luo, Jiaxin Guo, Daimeng Wei +7
This report outlines our approach for the WMT24 Discourse-Level Literary Translation Task, focusing on the Chinese-English language pair in the Constrained Track. Translating liter…
Multilingual Transfer and Domain Adaptation for Low-Resource Languages of Spain
Yuanchang Luo, Zhanglin Wu, Daimeng Wei +9
This article introduces the submission status of the Translation into Low-Resource Languages of Spain task at (WMT 2024) by Huawei Translation Service Center (HW-TSC). We participa…
Exploring the traditional NMT model and Large Language Model for chat translation
Jinlong Yang, Hengchao Shang, Daimeng Wei +10
This paper describes the submissions of Huawei Translation Services Center(HW-TSC) to WMT24 chat translation shared task on EnglishGermany (en-de) bidirection. The…
Machine Translation Advancements of Low-Resource Indian Languages by Transfer Learning
Bin Wei, Jiawei Zhen, Zongyao Li +10
This paper introduces the submission by Huawei Translation Center (HW-TSC) to the WMT24 Indian Languages Machine Translation (MT) Shared Task. To develop a reliable machine transla…
Choose the Final Translation from NMT and LLM hypotheses Using MBR Decoding: HW-TSC's Submission to the WMT24 General MT Shared Task
Zhanglin Wu, Daimeng Wei, Zongyao Li +7
This paper presents the submission of Huawei Translate Services Center (HW-TSC) to the WMT24 general machine translation (MT) shared task, where we participate in the English to Ch…
An End-to-End Speech Summarization Using Large Language Model
Hengchao Shang, Zongyao Li, Jiaxin Guo +5
Abstractive Speech Summarization (SSum) aims to generate human-like text summaries from spoken content. It encounters difficulties in handling long speech input and capturing the i…
Speaker-Smoothed kNN Speaker Adaptation for End-to-End ASR
Shaojun Li, Daimeng Wei, Hengchao Shang +7
Despite recent improvements in End-to-End Automatic Speech Recognition (E2E ASR) systems, the performance can degrade due to vocal characteristic mismatches between training and te…
A Novel Paradigm Boosting Translation Capabilities of Large Language Models
Jiaxin Guo, Hao Yang, Zongyao Li +3
This paper presents a study on strategies to enhance the translation capabilities of large language models (LLMs) in the context of machine translation (MT) tasks. The paper propos…
R-BI: Regularized Batched Inputs enhance Incremental Decoding Framework for Low-Latency Simultaneous Speech Translation
Jiaxin Guo, Zhanglin Wu, Zongyao Li +6
Incremental Decoding is an effective framework that enables the use of an offline model in a simultaneous setting without modifying the original model, making it suitable for Low-L…
INarIG: Iterative Non-autoregressive Instruct Generation Model For Word-Level Auto Completion
Hengchao Shang, Zongyao Li, Daimeng Wei +5
Computer-aided translation (CAT) aims to enhance human translation efficiency and is still important in scenarios where machine translation cannot meet quality requirements. One fu…