Dongdong Zhang

BlonDe: An Automatic Evaluation Metric for Document-level Machine Translation

2022 · Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies

Yuchen Jiang, Tianyu Liu, Shuming Ma, Dongdong Zhang, Jian Yang, Haoyang Huang, Rico Sennrich, Ryan Cotterell, Mrinmaya Sachan, Ming Zhou. Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational …

Revamping Multilingual Agreement Bidirectionally via Switched Back-translation for Multilingual Neural Machine Translation

2022 · arXiv (Cornell University)

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: (i) require parallel data between multiple language pairs, which is …

A Bilingual Parallel Corpus with Discourse Annotations

2022 · arXiv (Cornell University)

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. However, the development of document-level MT systems is hampered by …

HanoiT: Enhancing Context-aware Translation via Selective Context

2023 · arXiv (Cornell University)

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 trivial words may bring some noise and distract the …

Discourse Centric Evaluation of Machine Translation with a Densely Annotated Parallel Corpus

2023 · arXiv (Cornell University)

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, shifted its focus to document-level translation. Translating documents requires a deeper …

Language-Specific Neurons: The Key to Multilingual Capabilities in Large Language Models

2024 · arXiv (Cornell University)

Large language models (LLMs) demonstrate remarkable multilingual capabilities without being pre-trained on specially curated multilingual parallel corpora. It remains a challenging problem to explain the underlying mechanisms by which LLMs process multilingual texts. In this …

Early Warning Method for Gas Pipe Leakage Based on Multi-source Heterogeneous Data Fusion

2024

More and more pipeline leaks are causing irreparable effects. We present an early warning method for gas pipeline leakage based on multi-source heterogeneous data fusion. It the data layer, we categorize data and perform data …

Achieving Human Parity on Automatic Chinese to English News Translation

2018 · arXiv (Cornell University)

Machine translation has made rapid advances in recent years. Millions of people are using it today in online translation systems and mobile applications in order to communicate across language barriers. The question naturally arises whether …