Raphael Shu

According to our database, Raphael Shu authored at least 24 papers between 2016 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

User Simulation with Large Language Models for Evaluating Task-Oriented Dialogue.

Sam Davidson, Salvatore Romeo, Raphael Shu, James Gung, Arshit Gupta, Saab Mansour, Yi Zhang

CoRR, 2023

Intent Induction from Conversations for Task-Oriented Dialogue Track at DSTC 11.

James Gung, Raphael Shu, Emily Moeng, Wesley Rose, Salvatore Romeo, Yassine Benajiba, Arshit Gupta, Saab Mansour, Yi Zhang

CoRR, 2023

DiactTOD: Learning Generalizable Latent Dialogue Acts for Controllable Task-Oriented Dialogue Systems.

Qingyang Wu, James Gung, Raphael Shu, Yi Zhang

Proceedings of the 24th Meeting of the Special Interest Group on Discourse and Dialogue, 2023

Conversation Style Transfer using Few-Shot Learning.

Shamik Roy, Raphael Shu, Nikolaos Pappas, Elman Mansimov, Yi Zhang, Saab Mansour, Dan Roth

Proceedings of the 13th International Joint Conference on Natural Language Processing and the 3rd Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics, 2023

Pre-training Intent-Aware Encoders for Zero- and Few-Shot Intent Classification.

Mujeen Sung, James Gung, Elman Mansimov, Nikolaos Pappas, Raphael Shu, Salvatore Romeo, Yi Zhang, Vittorio Castelli

Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

2022

Improving Noised Gradient Penalty with Synchronized Activation Function for Generative Adversarial Networks.

Rui Yang, Raphael Shu, Hideki Nakayama

IEICE Trans. Inf. Syst., September, 2022

Dialog2API: Task-Oriented Dialogue with API Description and Example Programs.

Raphael Shu, Elman Mansimov, Tamer Alkhouli, Nikolaos Pappas, Salvatore Romeo, Arshit Gupta, Saab Mansour, Yi Zhang, Dan Roth

CoRR, 2022

Federated Semi-Supervised Learning with Prototypical Networks.

Woojung Kim, Keondo Park, Kihyuk Sohn, Raphael Shu, Hyung-Sin Kim

CoRR, 2022

2021

Reward Optimization for Neural Machine Translation with Learned Metrics.

Raphael Shu, Kang Min Yoo, Jung-Woo Ha

CoRR, 2021

GraphPlan: Story Generation by Planning with Event Graph.

Hong Chen, Raphael Shu, Hiroya Takamura, Hideki Nakayama

Proceedings of the 14th International Conference on Natural Language Generation, 2021

2020

Iterative Refinement in the Continuous Space for Non-Autoregressive Neural Machine Translation.

Jason Lee, Raphael Shu, Kyunghyun Cho

Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, 2020

Latent-Variable Non-Autoregressive Neural Machine Translation with Deterministic Inference Using a Delta Posterior.

Raphael Shu, Jason Lee, Hideki Nakayama, Kyunghyun Cho

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019

Enabling Real-time Neural IME with Incremental Vocabulary Selection.

Jiali Yao, Raphael Shu, Xinjian Li, Katsutoshi Ohtsuki, Hideki Nakayama

Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2019

Generating Diverse Translations with Sentence Codes.

Raphael Shu, Hideki Nakayama, Kyunghyun Cho

Proceedings of the 57th Conference of the Association for Computational Linguistics, 2019

2018

Real-time Neural-based Input Method.

Jiali Yao, Raphael Shu, Xinjian Li, Katsutoshi Ohtsuki, Hideki Nakayama

CoRR, 2018

Discrete Structural Planning for Neural Machine Translation.

Raphael Shu, Hideki Nakayama

CoRR, 2018

Compressing Word Embeddings via Deep Compositional Code Learning.

Raphael Shu, Hideki Nakayama

Proceedings of the 6th International Conference on Learning Representations, 2018

Improving Beam Search by Removing Monotonic Constraint for Neural Machine Translation.

Raphael Shu, Hideki Nakayama

Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics, 2018

2017

Single-Queue Decoding for Neural Machine Translation.

Raphael Shu, Hideki Nakayama

CoRR, 2017

Later-stage Minimum Bayes-Risk Decoding for Neural Machine Translation.

Raphael Shu, Hideki Nakayama

CoRR, 2017

An Empirical Study of Adequate Vision Span for Attention-Based Neural Machine Translation.

Raphael Shu, Hideki Nakayama

Proceedings of the First Workshop on Neural Machine Translation, 2017

2016

Reducing Redundant Computations with Flexible Attention.

Raphael Shu, Hideki Nakayama

CoRR, 2016

Generating Video Description using Sequence-to-sequence Model with Temporal Attention.

Natsuda Laokulrat, Sang Phan, Noriki Nishida, Raphael Shu, Yo Ehara, Naoaki Okazaki, Yusuke Miyao, Hideki Nakayama

Proceedings of the COLING 2016, 2016

Residual Stacking of RNNs for Neural Machine Translation.

Raphael Shu, Akiva Miura

Proceedings of the 3rd Workshop on Asian Translation, 2016