Name
Affiliation
Papers
MARINE CARPUAT
Univ Sci & Technol, Dept Comp Sci & Engn, Human Language Technol Ctr, HKUST, Hong Kong, Hong Kong, Peoples R China
84
Collaborators
Citations 
PageRank 
85
587
51.99
Referers 
Referees 
References 
1062
875
802
Search Limit
1001000
Title
Citations
PageRank
Year
An Imitation Learning Curriculum for Text Editing with Non-Autoregressive Models00.342022
Facilitating Global Team Meetings Between Language-Based Subgroups: When and How Can Machine Translation Help?00.342022
Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL 2022, Seattle, WA, United States, July 10-15, 202200.342022
Controlling Translation Formality Using Pre-trained Multilingual Language Models.00.342022
Can Synthetic Translations Improve Bitext Quality?00.342022
Evaluating the Evaluation Metrics for Style Transfer - A Case Study in Multilingual Formality Transfer.00.342021
A Non-Autoregressive Edit-Based Approach to Controllable Text Simplification.00.342021
Rule-based Morphological Inflection Improves Neural Terminology Translation.00.342021
EDITOR: An Edit-Based Transformer with Repositioning for Neural Machine Translation with Soft Lexical Constraints00.342021
How Does Distilled Data Complexity Impact the Quality and Confidence of Non-Autoregressive Machine Translation?00.342021
Leveraging Machine Translation to Support Distributed Teamwork Between Language-Based Subgroups: The Effects of Automated Keyword Tagging00.342021
Dual Reconstruction: a Unifying Objective for Semi-Supervised Neural Machine Translation00.342020
Controlling Neural Machine Translation Formality With Synthetic Supervision00.342020
The University of Maryland's Submissions to the WMT20 Chat Translation Task - Searching for More Data to Adapt Discourse-Aware Neural Machine Translation.00.342020
Generating Diverse Translations via Weighted Fine-tuning and Hypotheses Filtering for the Duolingo STAPLE Task00.342020
Detecting Fine-Grained Cross-Lingual Semantic Divergences without Supervision by Learning to Rank.00.342020
Controlling Text Complexity in Neural Machine Translation10.362019
Differentiable Sampling with Flexible Reference Word Order for Neural Machine Translation.00.342019
Curriculum Learning for Domain Adaptation in Neural Machine Translation.10.342019
The University of Maryland's Kazakh-English Neural Machine Translation System at WMT1900.342019
Weakly Supervised Cross-lingual Semantic Relation Classification via Knowledge Distillation10.352019
Identifying Fluently Inadequate Output in Neural and Statistical Machine Translation.00.342019
An Empirical Assessment of Machine Learning Approaches for Triaging Reports of a Java Static Analysis Tool10.342019
Bi-Directional Differentiable Input Reconstruction for Low-Resource Neural Machine Translation.00.342018
An Empirical Exploration of Curriculum Learning for Neural Machine Translation.10.362018
Multi-Task Neural Models for Translating Between Styles Within and Across Languages.00.342018
Fluency Over Adequacy: A Pilot Study in Measuring User Trust in Imperfect MT.10.352018
UMD at SemEval-2018 Task 10: Can Word Embeddings Capture Discriminative Attributes?00.342018
The University of Maryland's Chinese-English Neural Machine Translation Systems at WMT18.00.342018
Bi-Directional Neural Machine Translation with Synthetic Parallel Data.20.372018
Robust Cross-lingual Hypernymy Detection using Dependency Context.10.352018
Identifying Semantic Divergences in Parallel Text without Annotations.20.382018
Detecting Cross-Lingual Semantic Divergence for Neural Machine Translation.00.342017
A Study of Style in Machine Translation: Controlling the Formality of Machine Translation Output.60.442017
Detecting Asymmetric Semantic Relations in Context: A Case-Study on Hypernymy Detection.10.342017
Retrofitting Sense-Specific Word Vectors Using Parallel Text.20.352016
Learning Monolingual Compositional Representations Via Bilingual Supervision00.342016
Sparse Bilingual Word Representations for Cross-lingual Lexical Entailment.60.412016
Connotation in Translation.00.342015
Class-based N-gram language difference models for data selection.00.342015
Connotation in Translation10.342015
The UMD machine translation systems at IWSLT 2015.00.342015
The NRC System for Discriminating Similar Languages50.502014
CNRC-TMT: Second Language Writing Assistant System Description10.382014
Mixed Language and Code-Switching in the Canadian Hansard40.482014
Linear Mixture Models for Robust Machine Translation60.482014
Linear Mixture Models for Robust Machine Translation.00.342014
Assessing The Discourse Factors That Influence The Quality Of Machine Translation80.592014
Measuring Machine Translation Errors in New Domains.210.642013
FUN-NRC: Paraphrase-augmented Phrase-based SMT Systems for NTCIR-10 PatentMT.10.352013
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