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∙ 05/24/2023

How To Control Text Simplification? An Empirical Study of Control Tokens for Meaning Preserving Controlled Simplification

Text simplification rewrites text to be more readable for a specific aud...

0 Sweta Agrawal, et al. ∙

∙ 05/23/2023

What Else Do I Need to Know? The Effect of Background Information on Users' Reliance on AI Systems

AI systems have shown impressive performance at answering questions by r...

0 Navita Goyal, et al. ∙

∙ 01/18/2023

Understanding and Detecting Hallucinations in Neural Machine Translation via Model Introspection

Neural sequence generation models are known to "hallucinate", by produci...

0 Weijia Xu, et al. ∙

∙ 09/07/2022

Facilitating Global Team Meetings Between Language-Based Subgroups: When and How Can Machine Translation Help?

Global teams frequently consist of language-based subgroups who put toge...

0 Yongle Zhang, et al. ∙

∙ 05/13/2022

Controlling Translation Formality Using Pre-trained Multilingual Language Models

This paper describes the University of Maryland's submission to the Spec...

3 Elijah Rippeth, et al. ∙

∙ 03/17/2022

An Imitation Learning Curriculum for Text Editing with Non-Autoregressive Models

We propose a framework for training non-autoregressive sequence-to-seque...

0 Sweta Agrawal, et al. ∙

∙ 03/15/2022

Can Synthetic Translations Improve Bitext Quality?

Synthetic translations have been used for a wide range of NLP tasks prim...

0 Eleftheria Briakou, et al. ∙

∙ 10/20/2021

Evaluating the Evaluation Metrics for Style Transfer: A Case Study in Multilingual Formality Transfer

While the field of style transfer (ST) has been growing rapidly, it has ...

0 Eleftheria Briakou, et al. ∙

∙ 09/10/2021

Rule-based Morphological Inflection Improves Neural Terminology Translation

Current approaches to incorporating terminology constraints in machine t...

0 Weijia Xu, et al. ∙

∙ 06/09/2021

A Review of Human Evaluation for Style Transfer

This paper reviews and summarizes human evaluation practices described i...

0 Eleftheria Briakou, et al. ∙

∙ 05/31/2021

Beyond Noise: Mitigating the Impact of Fine-grained Semantic Divergences on Neural Machine Translation

While it has been shown that Neural Machine Translation (NMT) is highly ...

0 Eleftheria Briakou, et al. ∙

∙ 05/27/2021

How Does Distilled Data Complexity Impact the Quality and Confidence of Non-Autoregressive Machine Translation?

While non-autoregressive (NAR) models are showing great promise for mach...

0 Weijia Xu, et al. ∙

∙ 11/13/2020

EDITOR: an Edit-Based Transformer with Repositioning for Neural Machine Translation with Soft Lexical Constraints

We introduce an Edit-Based Transformer with Repositioning (EDITOR), whic...

0 Weijia Xu, et al. ∙

∙ 10/19/2020

Incorporating Terminology Constraints in Automatic Post-Editing

Users of machine translation (MT) may want to ensure the use of specific...

0 David Wan, et al. ∙

∙ 10/07/2020

Detecting Fine-Grained Cross-Lingual Semantic Divergences without Supervision by Learning to Rank

Detecting fine-grained differences in content conveyed in different lang...

0 Eleftheria Briakou, et al. ∙

∙ 10/07/2020

Dual Reconstruction: a Unifying Objective for Semi-Supervised Neural Machine Translation

While Iterative Back-Translation and Dual Learning effectively incorpora...

0 Weijia Xu, et al. ∙

∙ 11/20/2019

Controlling Neural Machine Translation Formality with Synthetic Supervision

This work aims to produce translations that convey source language conte...

0 Xing Niu, et al. ∙

∙ 11/03/2019

Controlling Text Complexity in Neural Machine Translation

This work introduces a machine translation task where the output is aime...

0 Sweta Agrawal, et al. ∙

∙ 05/14/2019

Curriculum Learning for Domain Adaptation in Neural Machine Translation

We introduce a curriculum learning approach to adapt generic neural mach...

0 Xuan Zhang, et al. ∙

∙ 04/04/2019

Differentiable Sampling with Flexible Reference Word Order for Neural Machine Translation

Despite some empirical success at correcting exposure bias in machine tr...

0 Weijia Xu, et al. ∙

∙ 11/02/2018

Bi-Directional Differentiable Input Reconstruction for Low-Resource Neural Machine Translation

We aim to better exploit the limited amounts of parallel text available ...

0 Xing Niu, et al. ∙

∙ 11/02/2018

An Empirical Exploration of Curriculum Learning for Neural Machine Translation

Machine translation systems based on deep neural networks are expensive ...

0 Xuan Zhang, et al. ∙

∙ 06/12/2018

Multi-Task Neural Models for Translating Between Styles Within and Across Languages

Generating natural language requires conveying content in an appropriate...

0 Xing Niu, et al. ∙

∙ 05/29/2018

Bi-Directional Neural Machine Translation with Synthetic Parallel Data

Despite impressive progress in high-resource settings, Neural Machine Tr...

0 Xing Niu, et al. ∙

∙ 03/30/2018

Robust Cross-lingual Hypernymy Detection using Dependency Context

Cross-lingual Hypernymy Detection involves determining if a word in one ...

0 Shyam Upadhyay, et al. ∙

∙ 03/29/2018

Identifying Semantic Divergences in Parallel Text without Annotations

Recognizing that even correct translations are not always semantically e...

0 Yogarshi Vyas, et al. ∙

∙ 02/16/2018

Fluency Over Adequacy: A Pilot Study in Measuring User Trust in Imperfect MT

Although measuring intrinsic quality has been a key factor in the advanc...

0 Marianna J. Martindale, et al. ∙

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