Shuming Ma

A New Recurrent Neural CRF for Learning Non-linear Edge Features

2016 · arXiv (Cornell University)

Conditional Random Field (CRF) and recurrent neural models have achieved success in structured prediction. More recently, there is a marriage of CRF and recurrent neural models, so that we can gain from both non-linear dense …

Automatic Academic Paper Rating Based on Modularized Hierarchical Convolutional Neural Network

2018 · arXiv (Cornell University)

As more and more academic papers are being submitted to conferences and journals, evaluating all these papers by professionals is time-consuming and can cause inequality due to the personal factors of the reviewers. In this …

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 …