activity
20232025
most citedR-BI: Regularized Batched Inputs enhance Incremental Decoding Framework for Low-Latency Simultaneous Speech Translation

2 citations · 3 across the 8 of their papers we have counts for

collaborators

8 papers

cs.CL2025

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…

cs.CL2025

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…

cs.CL2025

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…

cs.CL2025

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 (…

cs.CL2024

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…

cs.CL2024★ 2 cited

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…

cs.CL2023★ 1 cited

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…

cs.CL2023

Text Style Transfer Back-Translation

Daimeng Wei, Zhanglin Wu, Hengchao Shang +6

Back Translation (BT) is widely used in the field of machine translation, as it has been proved effective for enhancing translation quality. However, BT mainly improves the transla…