Monday, November 4

Proceedings:

• https://www.aclweb.org/anthology/events/emnlp-2019/#d19-56

List of Accepted Papers*

• A Margin-based Loss with Synthetic Negative Samples for Continuous-output Machine Translation

Gayatri Bhat, Sachin Kumar and Yulia Tsvetkov

• Adaptively Scheduled Multitask Learning: The Case of Low-Resource Neural Machine Translation

Poorya Zaremoodi and Gholamreza Haffari

• Attending to Future Tokens for Bidirectional Sequence Generation

Carolin Lawrence, Bhushan Kotnis and Mathias Niepert

• Auto-Sizing the Transformer Network: Improving Speed, Efficiency, and Performance for Low-Resource Machine Translation

Kenton Murray, Jeffery Kinnison, Toan Q. Nguyen, Walter Scheirer and David Chiang

• Auto-Sizing the Transformer Network: Shrinking Parameters for the WNGT 2019 Efficiency Task

Kenton Murray, Brian DuSell and David Chiang

• Automated Generation of Search Advertisements

Jia Ying Jen, Divish Dayal, Corinne Choo, Ashish Awasthi, Audrey Kuah and Ziheng Lin

• Big Bidirectional Insertion Representations for Documents

Lala Li and William Chan

• Context-Aware Learning for Neural Machine Translation

Sébastien Jean and Kyunghyun Cho

• Controlled Text Generation for Data Augmentation in Intelligent Artificial Agents

Nikolaos Malandrakis, Minmin Shen, Anuj Goyal, Shuyang Gao, Abhishek Sethi and Angeliki Metallinou

• Decomposing Textual Information For Style Transfer

Ivan P. Yamshchikov, Viacheslav Shibaev, Aleksander Nagaev, Jürgen Jost and Alexey Tikhonov

• Domain Differential Adaptation for Neural Machine Translation

Zi-Yi Dou, Xinyi Wang, Junjie Hu and Graham Neubig

• Enhanced Transformer Model for Data-to-Text Generation

Li Gong, Josep Crego and Jean Senellart

• From Research to Production and Back: Fast and Accurate Neural Machine Translation

Young Jin Kim, Marcin Junczys-Dowmunt and Hany Hassan

• Generalization in Generation: A closer look at Exposure Bias

Florian Schmidt

• Generating a Common Question from Multiple Documents using Multi-source Encoder-Decoder Models

Woon Sang Cho, Yizhe Zhang, Sudha Rao, Chris Brockett and Sungjin Lee

• Generating Diverse Story Continuations with Controllable Semantics

Lifu Tu, Xiaoan Ding, Dong Yu and Kevin Gimpel

• Hello, It's GPT-2 - How Can I Help You? Towards the Use of Pretrained Language Models for Task-Oriented Dialogue Systems

Paweł Budzianowski and Ivan Vulić

• Improved Variational Neural Machine Translation via Promoting Mutual Information

Xian Li, Jiatao Gu, Ning Dong and Arya D. McCarthy

• Insertion-Deletion Transformer

Laura Ruis, Mitchell Stern, Julia Proskurnia and William Chan

• Interrogating the Explanatory Power of Attention in Neural Machine Translation

Pooya Moradi, Nishant Kambhatla and Anoop Sarkar

• Latent Relation Language Models

Hiroaki Hayashi, Zecong Hu, Chenyan Xiong and Graham Neubig

• Learning to Generate Word- and Phrase-Embeddings for Efficient Phrase-Based Neural Machine Translation

Chan Young Park and Yulia Tsvetkov

• Machine Translation of Restaurant Reviews: New Corpus for Domain Adaptation and Robustness

Alexandre Berard, Ioan Calapodescu, Marc Dymetman, Claude Roux, Jean-Luc Meunier and Vassilina Nikoulina

• Making Asynchronous Stochastic Gradient Descent Work for Transformers

Alham Fikri Aji and Kenneth Heafield

• Mixed Multi-Head Self-Attention for Neural Machine Translation

Hongyi Cui, Shohei Iida, Po-Hsuan Hung, Takehito Utsuro and Masaaki Nagata

• Monash University’s Submissions to the WNGT 2019 Document Translation Task

Sameen Maruf and Gholamreza Haffari

• Multilingual KERMIT: It’s Not Easy Being Generative

Harris Chan, Jamie Kiros and William Chan

• Naver Labs Europe’s Systems for the Document-Level Generation and Translation Task at WNGT 2019

Fahimeh Saleh, Alexandre Berard, Ioan Calapodescu and Laurent Besacier

• On the Importance of the Kullback-Leibler Divergence Term in Variational Autoencoders for Text Generation

Victor Prokhorov, Ehsan Shareghi, Yingzhen Li, Mohammad Taher Pilehvar and Nigel Collier

• On the Importance of Word Boundaries in Character-level Neural Machine Translation

Duygu Ataman, Orhan Firat, Mattia A. Di Gangi, Marcello Federico and Alexandra Birch

• On the use of BERT for Neural Machine Translation

Stephane Clinchant, Kweon Woo Jung and Vassilina Nikoulina

• Paraphrasing with Large Language Models

Sam Witteveen and Martin Andrews

• Positional Encoding to Control Output Sequence Length

Sho Takase and Naoaki Okazaki

• Recycling a Pre-trained BERT Encoder for Neural Machine Translation

Kenji Imamura and Eiichiro Sumita

• Selecting, Planning, and Rewriting: A modular approach for Data-to-text Generation

Lesly Miculicich, Marc Marone and Hany Hassan

• SYSTRAN @ WNGT 2019: DGT Task

Li Gong, Josep Crego and Jean Senellart

• The Daunting Task of Actual (Not Operational) Textual Style Transfer Auto-Evaluation

Richard Yuanzhe Pang

• Transformer and seq2seq model for Paraphrase Generation

Elozino Egonmwan and Yllias Chali

• Transformer-based Model for Single Documents Neural Summarization

Elozino Egonmwan and Yllias Chali

• Two Birds, One Stone: A Simple, Unified Model for Text Generation from Structured and Unstructured Data

Hamidreza Shahidi, Ming Li and Jimmy Lin

• University of Edinburgh’s submission to the Document-level Generation and Translation Shared Task

Ratish Puduppully, Jonathan Mallinson and Mirella Lapata

• Unsupervised Evaluation Metrics and Learning Criteria for Non-Parallel Textual Transfer

Richard Yuanzhe Pang and Kevin Gimpel

• Zero-Resource Neural Machine Translation with Monolingual Pivot Data

Anna Currey and Kenneth Heafield