9 citations · 20 across the 11 of their papers we have counts for
11 papers
Communication-Efficient Personalized Federated Learning for Speech-to-Text Tasks
Yichao Du, Zhirui Zhang, Linan Yue +5
To protect privacy and meet legal regulations, federated learning (FL) has gained significant attention for training speech-to-text (S2T) systems, including automatic speech recogn…
Lost in the Source Language: How Large Language Models Evaluate the Quality of Machine Translation
Xu Huang, Zhirui Zhang, Xiang Geng +3
This study investigates how Large Language Models (LLMs) leverage source and reference data in machine translation evaluation task, aiming to better understand the mechanisms behin…
IMTLab: An Open-Source Platform for Building, Evaluating, and Diagnosing Interactive Machine Translation Systems
Xu Huang, Zhirui Zhang, Ruize Gao +6
We present IMTLab, an open-source end-to-end interactive machine translation (IMT) system platform that enables researchers to quickly build IMT systems with state-of-the-art model…
FedJudge: Federated Legal Large Language Model
Linan Yue, Qi Liu, Yichao Du +3
Large Language Models (LLMs) have gained prominence in the field of Legal Intelligence, offering potential applications in assisting legal professionals and laymen. However, the ce…
Nearest Neighbor Machine Translation is Meta-Optimizer on Output Projection Layer
Ruize Gao, Zhirui Zhang, Yichao Du +2
Nearest Neighbor Machine Translation (NN-MT) has achieved great success in domain adaptation tasks by integrating pre-trained Neural Machine Translation (NMT) models with domain…
Federated Nearest Neighbor Machine Translation
Yichao Du, Zhirui Zhang, Bingzhe Wu +3
To protect user privacy and meet legal regulations, federated learning (FL) is attracting significant attention. Training neural machine translation (NMT) models with traditional F…
Simple and Scalable Nearest Neighbor Machine Translation
Yuhan Dai, Zhirui Zhang, Qiuzhi Liu +4
NN-MT is a straightforward yet powerful approach for fast domain adaptation, which directly plugs pre-trained neural machine translation (NMT) models with domain-specific token-…
Non-Parametric Domain Adaptation for End-to-End Speech Translation
Yichao Du, Weizhi Wang, Zhirui Zhang +4
End-to-End Speech Translation (E2E-ST) has received increasing attention due to the potential of its less error propagation, lower latency, and fewer parameters. However, the effec…
Regularizing End-to-End Speech Translation with Triangular Decomposition Agreement
Yichao Du, Zhirui Zhang, Weizhi Wang +3
End-to-end speech-to-text translation (E2E-ST) is becoming increasingly popular due to the potential of its less error propagation, lower latency, and fewer parameters. Given the t…
Rethinking Zero-shot Neural Machine Translation: From a Perspective of Latent Variables
Weizhi Wang, Zhirui Zhang, Yichao Du +3
Zero-shot translation, directly translating between language pairs unseen in training, is a promising capability of multilingual neural machine translation (NMT). However, it usual…
Inheritance-guided Hierarchical Assignment for Clinical Automatic Diagnosis
Yichao Du, Pengfei Luo, Xudong Hong +5
Clinical diagnosis, which aims to assign diagnosis codes for a patient based on the clinical note, plays an essential role in clinical decision-making. Considering that manual diag…