18 citations · 96 across the 18 of their papers we have counts for
18 papers
Multilingual Non-Autoregressive Machine Translation without Knowledge Distillation
Chenyang Huang, Fei Huang, Zaixiang Zheng +3
Multilingual neural machine translation (MNMT) aims at using one single model for multiple translation directions. Recent work applies non-autoregressive Transformers to improve th…
Diffusion Language Models Are Versatile Protein Learners
Xinyou Wang, Zaixiang Zheng, Fei Ye +3
This paper introduces diffusion protein language model (DPLM), a versatile protein language model that demonstrates strong generative and predictive capabilities for protein sequen…
Diffusion Language Models Can Perform Many Tasks with Scaling and Instruction-Finetuning
Jiasheng Ye, Zaixiang Zheng, Yu Bao +2
The recent surge of generative AI has been fueled by the generative power of diffusion probabilistic models and the scalable capabilities of large language models. Despite their po…
Structure-informed Language Models Are Protein Designers
Zaixiang Zheng, Yifan Deng, Dongyu Xue +3
This paper demonstrates that language models are strong structure-based protein designers. We present LM-Design, a generic approach to reprogramming sequence-based protein language…
DINOISER: Diffused Conditional Sequence Learning by Manipulating Noises
Jiasheng Ye, Zaixiang Zheng, Yu Bao +2
While diffusion models have achieved great success in generating continuous signals such as images and audio, it remains elusive for diffusion models in learning discrete sequence…
Helping the Weak Makes You Strong: Simple Multi-Task Learning Improves Non-Autoregressive Translators
Xinyou Wang, Zaixiang Zheng, Shujian Huang
Recently, non-autoregressive (NAR) neural machine translation models have received increasing attention due to their efficient parallel decoding. However, the probabilistic framewo…
The Volctrans GLAT System: Non-autoregressive Translation Meets WMT21
Lihua Qian, Yi Zhou, Zaixiang Zheng +7
This paper describes the Volctrans' submission to the WMT21 news translation shared task for German->English translation. We build a parallel (i.e., non-autoregressive) translation…
DirectQE: Direct Pretraining for Machine Translation Quality Estimation
Qu Cui, Shujian Huang, Jiahuan Li +4
Machine Translation Quality Estimation (QE) is a task of predicting the quality of machine translations without relying on any reference. Recently, the predictor-estimator framewor…
Duplex Sequence-to-Sequence Learning for Reversible Machine Translation
Zaixiang Zheng, Hao Zhou, Shujian Huang +3
Sequence-to-sequence learning naturally has two directions. How to effectively utilize supervision signals from both directions? Existing approaches either require two separate mod…
Vocabulary Learning via Optimal Transport for Neural Machine Translation
Jingjing Xu, Hao Zhou, Chun Gan +2
The choice of token vocabulary affects the performance of machine translation. This paper aims to figure out what is a good vocabulary and whether one can find the optimal vocabula…
RPD: A Distance Function Between Word Embeddings
Xuhui Zhou, Zaixiang Zheng, Shujian Huang
It is well-understood that different algorithms, training processes, and corpora produce different word embeddings. However, less is known about the relation between different embe…
Towards Making the Most of Context in Neural Machine Translation
Zaixiang Zheng, Xiang Yue, Shujian Huang +2
Document-level machine translation manages to outperform sentence level models by a small margin, but have failed to be widely adopted. We argue that previous research did not make…
Multi-Perspective Inferrer: Reasoning Sentences Relationship from Holistic Perspective
Zhen Cheng, Zaixiang Zheng, Xin-Yu Dai +2
Natural Language Inference (NLI) aims to determine the logic relationships (i.e., entailment, neutral and contradiction) between a pair of premise and hypothesis. Recently, the ali…
Learning Representation Mapping for Relation Detection in Knowledge Base Question Answering
Peng Wu, Shujian Huang, Rongxiang Weng +4
Relation detection is a core step in many natural language process applications including knowledge base question answering. Previous efforts show that single-fact questions could…
Dynamic Past and Future for Neural Machine Translation
Zaixiang Zheng, Shujian Huang, Zhaopeng Tu +2
Previous studies have shown that neural machine translation (NMT) models can benefit from explicitly modeling translated (Past) and untranslated (Future) to groups of translated an…
Learning to Discriminate Noises for Incorporating External Information in Neural Machine Translation
Zaixiang Zheng, Shujian Huang, Zewei Sun +3
Previous studies show that incorporating external information could improve the translation quality of Neural Machine Translation (NMT) systems. However, there are inevitably noise…
Modeling Past and Future for Neural Machine Translation
Zaixiang Zheng, Hao Zhou, Shujian Huang +4
Existing neural machine translation systems do not explicitly model what has been translated and what has not during the decoding phase. To address this problem, we propose a novel…
Neural Machine Translation with Word Predictions
Rongxiang Weng, Shujian Huang, Zaixiang Zheng +2
In the encoder-decoder architecture for neural machine translation (NMT), the hidden states of the recurrent structures in the encoder and decoder carry the crucial information abo…