566 citations · 883 across the 35 of their papers we have counts for
36 papers
On the Off-Target Problem of Zero-Shot Multilingual Neural Machine Translation
Liang Chen, Shuming Ma, Dongdong Zhang +2
While multilingual neural machine translation has achieved great success, it suffers from the off-target issue, where the translation is in the wrong language. This problem is more…
One-stop Training of Multiple Capacity Models
Lan Jiang, Haoyang Huang, Dongdong Zhang +2
Training models with varying capacities can be advantageous for deploying them in different scenarios. While high-capacity models offer better performance, low-capacity models requ…
Discourse Centric Evaluation of Machine Translation with a Densely Annotated Parallel Corpus
Yuchen Eleanor Jiang, Tianyu Liu, Shuming Ma +3
Several recent papers claim human parity at sentence-level Machine Translation (MT), especially in high-resource languages. Thus, in response, the MT community has, in part, shifte…
Target-Agnostic Gender-Aware Contrastive Learning for Mitigating Bias in Multilingual Machine Translation
Minwoo Lee, Hyukhun Koh, Kang-il Lee +3
Gender bias is a significant issue in machine translation, leading to ongoing research efforts in developing bias mitigation techniques. However, most works focus on debiasing bili…
Not All Languages Are Created Equal in LLMs: Improving Multilingual Capability by Cross-Lingual-Thought Prompting
Haoyang Huang, Tianyi Tang, Dongdong Zhang +4
Large language models (LLMs) demonstrate impressive multilingual capability, but their performance varies substantially across different languages. In this work, we introduce a sim…
Chain-of-Dictionary Prompting Elicits Translation in Large Language Models
Hongyuan Lu, Haoran Yang, Haoyang Huang +3
Large language models (LLMs) have shown surprisingly good performance in multilingual neural machine translation (MNMT) even when trained without parallel data. Yet, despite the fa…
On the Pareto Front of Multilingual Neural Machine Translation
Liang Chen, Shuming Ma, Dongdong Zhang +2
In this work, we study how the performance of a given direction changes with its sampling ratio in Multilingual Neural Machine Translation (MNMT). By training over 200 multilingual…
Are More Layers Beneficial to Graph Transformers?
Haiteng Zhao, Shuming Ma, Dongdong Zhang +2
Despite that going deep has proven successful in many neural architectures, the existing graph transformers are relatively shallow. In this work, we explore whether more layers are…
HanoiT: Enhancing Context-aware Translation via Selective Context
Jian Yang, Yuwei Yin, Shuming Ma +7
Context-aware neural machine translation aims to use the document-level context to improve translation quality. However, not all words in the context are helpful. The irrelevant or…
GanLM: Encoder-Decoder Pre-training with an Auxiliary Discriminator
Jian Yang, Shuming Ma, Li Dong +7
Pre-trained models have achieved remarkable success in natural language processing (NLP). However, existing pre-training methods underutilize the benefits of language understanding…
Advancing Multilingual Pre-training: TRIP Triangular Document-level Pre-training for Multilingual Language Models
Hongyuan Lu, Haoyang Huang, Shuming Ma +3
Despite the success of multilingual sequence-to-sequence pre-training, most existing approaches rely on document-level monolingual corpora in many different languages, sentence-lev…
LVP-M3: Language-aware Visual Prompt for Multilingual Multimodal Machine Translation
Hongcheng Guo, Jiaheng Liu, Haoyang Huang +5
Multimodal Machine Translation (MMT) focuses on enhancing text-only translation with visual features, which has attracted considerable attention from both natural language processi…
A Bilingual Parallel Corpus with Discourse Annotations
Yuchen Eleanor Jiang, Tianyu Liu, Shuming Ma +3
Machine translation (MT) has almost achieved human parity at sentence-level translation. In response, the MT community has, in part, shifted its focus to document-level translation…
CROP: Zero-shot Cross-lingual Named Entity Recognition with Multilingual Labeled Sequence Translation
Jian Yang, Shaohan Huang, Shuming Ma +6
Named entity recognition (NER) suffers from the scarcity of annotated training data, especially for low-resource languages without labeled data. Cross-lingual NER has been proposed…
Revamping Multilingual Agreement Bidirectionally via Switched Back-translation for Multilingual Neural Machine Translation
Hongyuan Lu, Haoyang Huang, Shuming Ma +3
Despite the fact that multilingual agreement (MA) has shown its importance for multilingual neural machine translation (MNMT), current methodologies in the field have two shortages…
UM4: Unified Multilingual Multiple Teacher-Student Model for Zero-Resource Neural Machine Translation
Jian Yang, Yuwei Yin, Shuming Ma +5
Most translation tasks among languages belong to the zero-resource translation problem where parallel corpora are unavailable. Multilingual neural machine translation (MNMT) enable…
HLT-MT: High-resource Language-specific Training for Multilingual Neural Machine Translation
Jian Yang, Yuwei Yin, Shuming Ma +3
Multilingual neural machine translation (MNMT) trained in multiple language pairs has attracted considerable attention due to fewer model parameters and lower training costs by sha…
GTrans: Grouping and Fusing Transformer Layers for Neural Machine Translation
Jian Yang, Yuwei Yin, Liqun Yang +5
Transformer structure, stacked by a sequence of encoder and decoder network layers, achieves significant development in neural machine translation. However, vanilla Transformer mai…
DeepNet: Scaling Transformers to 1,000 Layers
Hongyu Wang, Shuming Ma, Li Dong +3
In this paper, we propose a simple yet effective method to stabilize extremely deep Transformers. Specifically, we introduce a new normalization function (DeepNorm) to modify the r…
Zero-shot Cross-lingual Transfer of Prompt-based Tuning with a Unified Multilingual Prompt
Lianzhe Huang, Shuming Ma, Dongdong Zhang +2
Prompt-based tuning has been proven effective for pretrained language models (PLMs). While most of the existing work focuses on the monolingual prompts, we study the multilingual p…
SMDT: Selective Memory-Augmented Neural Document Translation
Xu Zhang, Jian Yang, Haoyang Huang +4
Existing document-level neural machine translation (NMT) models have sufficiently explored different context settings to provide guidance for target generation. However, little att…
PAEG: Phrase-level Adversarial Example Generation for Neural Machine Translation
Juncheng Wan, Jian Yang, Shuming Ma +4
While end-to-end neural machine translation (NMT) has achieved impressive progress, noisy input usually leads models to become fragile and unstable. Generating adversarial examples…
Multilingual Machine Translation Systems from Microsoft for WMT21 Shared Task
Jian Yang, Shuming Ma, Haoyang Huang +8
This report describes Microsoft's machine translation systems for the WMT21 shared task on large-scale multilingual machine translation. We participated in all three evaluation tra…
Towards Making the Most of Multilingual Pretraining for Zero-Shot Neural Machine Translation
Guanhua Chen, Shuming Ma, Yun Chen +4
This paper demonstrates that multilingual pretraining and multilingual fine-tuning are both critical for facilitating cross-lingual transfer in zero-shot translation, where the neu…