Professor, Ph. D. Advisor
Natural Language Processing Research Group
National Key Laboratory of Novel Software Technology
School of Computer Science, Nanjing University
[Correspondence] [Biography] [Recruiting] [Research Interests] [Academic Services] [Honors and Awards] [Courses] [Presentations] [Selected Publication]
Office:
Room 902, Computer Science and Technology Building, Xianlin Campus of Nanjing University
163 Xianlin Avenue, Nanjing 210023, China
E-mail:
huangsj at nju dot edu dot cn
Currently, I am a professor and Ph. D. Advisor in School of Computer Science (formerly known as the Department of Computer Science and Technology) of Nanjing University, member of the National Key Laboratory of Novel Software Technology.
I received my B.Sc. degree and Ph. D. in Computer Science in Jun. 2006 and Jun. 2012 from Nanjing University, respectively. I am a member of NLP Group since undergraduate in Sep. 2005, led by Prof. Jiajun Chen. During my Ph. D. study, I spent 11 months (from Oct. 2007 to Aug. 2008) as visiting student in NLC group, MSRA, where I worked with Long Jiang in Chinese Couplet project and in SMT team with Mu Li, Henry Li and Dongdong Zhang. I also spent 12 months as a visiting student in InterACT lab, LTI, CMU, working with Prof. Stephan Vogel.
I was awarded the Excellent Young Scholar Research Project by Jiangsu Provincial Research Foundation in 2017, CCF-NLPCC Young Outstanding Scientist Award in 2020, CIPSC Hanwang Youth Innovation Award in 2022. Our alumni Hao Zhou, Zaixiang Zheng, Yu Bao (co-advised with Prof. Jiajun Chen) were awarded Best Ph. D. Thesis Awards.
Our translation quality estimation research and systems won the first place in WMT2022 QE subtasks (word-level MQM (En-De), sentence-level MQM (En-De)) and all 3 tasks in En-De direction in WMT2023 QE (word-level MQM, sentence-level MQM, error span detection).
Our paper is recognized as the Outstanding Paper in EMNLP 2024 (Congrats to Jiahuan and Yiqing!).
I am looking for highly motivated undergraduate students to work together on NLP problems. If you have no NLP background, please consider taking our course (Machine Translation and Natural Langauge Generation, every spring, for sophomores in Nanjing University) or joining our NLP summer camp first (every summer, mainly for freshman or sophomore). There are some talks about our research on bilibili.com. Please also take a look before you apply.
We are also expecting post-doc researchers to work together on NLP research or applications.
I am terribly sorry for not being able to reply all emails applying for a Ph.D. position (overwhelmed by the applications). My reply is usually fast. Please consider me as unavailable if no reply within 3~4 working days.
My research is supported by projects from National Natural Science Foundation of China (NSFC), National Key R&D Program of China and the Jiangsu Provincial Research Foundation for Basic Research. We also have wide collaborations with industrial labs in Baidu, Tencent, Alibaba, ByteDance, Huawei, ZTE, China Mobile, etc.
My research interests lie in natural language processing (NLP), one of the hottest and most fundamental challenges in artificial intelligence, which is to automatically understand and generate natural language texts. My group and I are working on problems such as machine translation, summarization, question answering, etc. These problems usually require a deep understanding of languages, as well as the ability of fluent generation. Previous attempts to these problems involve lexical/syntactic/semantic analysis of natural language texts. Nowadays, the development of pretrained models and large language models (LLMs) provides other possibilities.
We are particularly interested in designing and applying statistical methods/models (including deep learning models, LLMs) for these problems. Currently, we mainly focus on the following topics:
- Language/Intelligent Abilities of LLM. We’re trying to understand the abilities of LLMs, including the abilities for language comprehension, in-context learning, logic reasoning, mathematical computation, long-context learning, as well as the ability of working as intelligent agents for a given task. It is interesting and also important to know how these abilities are obtained, how they are applied to specific tasks and how to improve them if needed.
- LLM and Multilingualism (Multilingual LLM). We’re trying to understand and improve the relation of language abilities across different languages. It is important to improve the language ability for Chinese and relatively low resource languages. In the end, we aim at building language models that are equally effective for all languages.
- Machine Translation. We’re investigating various methods to improve the capacity of multilingualism, by designing novel machine translation architectures with the help of both task-specific models and LLMs, evaluating/estimating the quality of machine translation, bringing human into the learning loop, improving translation performance for low-resource language pairs or domains, etc.
- Natural Language Generation. We’re modelling different natural language generation tasks, e.g., summarization, paraphrasing, text style transfer, text simplification, answering questions with natural text, dialog, etc. Certain controlling factors need to be considered for a specific generation task, which brings interesting challenges. Other topics for generation include the evaluation, factual consistency and explainability, etc.
- Interdisciplinary Application of NLP/NLG. We’re actively applying the techniques of machine translation and natural language processing in interdisciplinary research. For example, to analyze ancient Chinese, to generate or translate ancient Chinese, to understand the language comprehension process of human brain, etc.
in Autumn semester, for undergraduate students.
in Spring semester, for undergraduate students.
in Spring semester, for undergraduate students.
in Autumn semester, for graduate students.
in Spring semester, for both undergraduate and graduate students.
(mostly in Chinese, hosted on bilibili.com)
Knowledge Learning in Large Languae Models (80 mins, video). Invited talk at HIT-SZ. 2024-11.
Multilingual LLM Research from an MT perspective (20 mins, video). Invited talk at CCMT-2024. 2024-11.
Application of the Multilingual Ability of Large Language Models (50 mins, video). Invited talk at HIT-SZ (later at Huawei, CLLM2024), 2024-05.
Exploring the Multilingual Ability of Large Language Models (60 mins, video). Invited talk at Bytedance. 2023-08.
Analyzing Multilingual Machine Translation Ability of Large Language Models (30 min, video). Invited talk at HIT. 2023-04.
Natural Language Generation with Latent Variables (75 mins, video). Invited Talk at FDU. 2020-06.
Research and Challenges of Multilingual Large Language Models (50 mins, video, slides). Tutorial Talk at NLPCC2024. 2024-10.
Research Development of Multilingualism in the Era of LLM (15 mins, video). Invited talk at the Frontier Research Overview session, CCL2024. 2024-07.
Research Development of Machine translation and Large Language Model (15 mins, video). Invited talk at the Frontier Research Overview session, CCL2023. 2023-08.
kNN Machine Translation. Tutorial at NLPCC2022 (75 mins, video, slides) and later at MLNLP2022 (video).
Quality Estimation for Machine Translation (100 mins, video). Invited talk at MTPE workshop. 2022-02 (updated 2023-05).
Large Language Models and Applications (2 hours, video). Lecture at NJUNLP SummerCamp2024. 2024-07.
Machine Translation and Multilingual LLMs (2 hours, video). Lecture at NJUNLP SummerCamp2024. 2024-07.
Introduction to Machine Translation (90 mins, video). Lecture at NJUNLP SummerCamp 2023. 2023-07.
A More Complete List on Google Scholar
* marks corresponding author(s).
2025
MoE-LPR: Multilingual Extension of Large Language Models through Mixture-of-Experts with Language Priors Routing.
Hao Zhou, Zhijun Wang, Shujian Huang*, Xin Huang, Xue Han, Junlan Feng, Chao Deng, Weihua Luo, Jiajun Chen.
Accepted by AAAI 2025. (arXiv:2408.11396, code)
Enforcing Paraphrase Generation via Controllable Latent Diffusion.
Wei Zou, Ziyuan Zhuang, Shujian Huang*, Jia Liu, Jiajun Chen.
Accepted by Frontiers of Computer Science. (arXiv:2404.08938, code)
2024
Formality is Favored: Unraveling the Learning Preferences of Large Language Models on Data with Conflicting Knowledge.
Jiahuan Li, Yiqing Cao, Shujian Huang*, Jiajun Chen.
EMNLP 2024. Outstanding Paper Award (5+20/1271/6105). (arXiv:2410.04784, video, code)
Hallu-PI: Evaluating Hallucination in Multi-modal Large Language Models within Perturbed Inputs.
Peng Ding, Jingyu Wu, Jun Kuang, Dan Ma, Xuezhi Cao, Xunliang Cai, Shi Chen, Jiajun Chen, Shujian Huang*.
ACM MM 2024. (arXiv:2408.01355, code)
PreAlign: Boosting Cross-Lingual Transfer by Early Establishment of Multilingual Alignment.
Jiahuan Li, Shujian Huang*, Xinyu Dai, Jiajun Chen.
EMNLP 2024. (arXiv:2407.16222, video, code)
Multilingual Contrastive Decoding via Language-Agnostic Layers Skipping.
Wenhao Zhu, Sizhe Liu, Shujian Huang*, Shuaijie She, Chris Wendler, Jiajun Chen.
Findings of EMNLP 2024. (arXiv:2407.10795, code)
Large Language Models Are Cross-Lingual Knowledge-Free Reasoners.
Peng Hu, Sizhe Liu, Changjiang Gao, Xin Huang, Xue Han, Junlan Feng, Chao Deng, Shujian Huang*.
arXiv:2406.16655 (video , code)
Limited Out-of-Context Knowledge Reasoning in Large Language Models.
Peng Hu, Changjiang Gao, Ruiqi Gao, Jiajun Chen, Shujian Huang*.
Findings of EMNLP 2024. (arXiv:2406.07393, code)
Why Not Transform Chat Large Language Models to Non-English?.
Xiang Geng, Ming Zhu, Jiahuan Li, Zhejian Lai, Wei Zou, Shuaijie She, Jiaxin Guo, Xiaofeng Zhao, Yinglu Li, Yuang Li, Chang Su, Yanqing Zhao, Xinglin Lyu, Min Zhang, Jiajun Chen, Hao Yang, Shujian Huang*.
arXiv:2405.13923 (code)
Getting More from Less: Large Language Models are Good Spontaneous Multilingual Learners.
Shimao Zhang, Changjiang Gao, Wenhao Zhu, Jiajun Chen, Xin Huang, Xue Han, Junlan Feng, Chao Deng, Shujian Huang*.
EMNLP 2024. arXiv:2405.13816
The Power of Question Translation Training in Multilingual Reasoning: Broadened Scope and Deepened Insights.
Wenhao Zhu, Shujian Huang*, Fei Yuan, Jiajun Chen, Alexandra Birch.
arXiv:2405.01345 (code)
Diffusion Language Models Are Versatile Protein Learners.
Xinyou Wang, Zaixiang Zheng, Fei Ye, Dongyu Xue, Shujian Huang, Quanquan Gu*.
ICML 2024. (arXiv:2402.18567)
Measuring Meaning Composition in the Human Brain with Composition Scores from Large Language Models.
Changjiang Gao, Jixing Li*, Jiajun Chen, Shujian Huang*.
ACL 2024. (arXiv:2403.04325, code)
Question Translation Training for Better Multilingual Reasoning.
Wenhao Zhu, Shujian Huang*, Fei Yuan, Shuaijie She, Jiajun Chen, Alexandra Birch.
Findings of ACL 2024. (arXiv:2401.07817, code)
MAPO: Advancing Multilingual Reasoning through Multilingual Alignment-as-Preference Optimization.
Shuaijie She, Wei Zou, Shujian Huang*, Wenhao Zhu, Xiang Liu, Xiang Geng, Jiajun Chen.
ACL 2024. (arXiv:2401.06838, code)
Multi-Candidate Speculative Decoding.
Sen Yang, Shujian Huang*, Xinyu Dai, Jiajun Chen.
arXiv:2401.06706 (code)
Lost in the Source Language: How Large Language Models Evaluate the Quality of Machine Translation.
Xu Huang, Zhirui Zhang*, Xiang Geng, Yichao Du, Jiajun Chen, Shujian Huang*.
Findings of ACL 2024. (arXiv:2401.06568, code)
Multilingual Pretraining and Instruction Tuning Improve Cross-Lingual Knowledge Alignment, But Only Shallowly.
Changjiang Gao, Hongda Hu, Peng Hu, Jiajun Chen, Jixing Li, Shujian Huang*.
NAACL 2024. (arXiv:2403.04325)
MT-PATCHER: Selective and Extendable Knowledge Distillation from Large Language Models for Machine Translation.
Jiahuan Li, Shanbo Cheng, Shujian Huang*, Jiajun Chen.
NAACL 2024. (arXiv:2403.09522, code)
A Wolf in Sheep’s Clothing: Generalized Nested Jailbreak Prompts can Fool Large Language Models Easily.
Peng Ding, Jun Kuang, Dan Ma, Xuezhi Cao, Yunsen Xian, Jiajun Chen, Shujian Huang*.
NAACL 2024. (arXiv:2311.08268, code)
Exploring the Factual Consistency in Dialogue Comprehension of Large Language Models.
Shuaijie She, Shujian Huang*, Xingyun Wang, Yanke Zhou, Jiajun Chen.
NAACL 2024. (arXiv:2311.07194, code)
Multilingual Machine Translation with Large Language Models: Empirical Results and Analysis.
Wenhao Zhu, Hongyi Liu, Qingxiu Dong, Jingjing Xu, Shujian Huang*, Lingpeng Kong, Jiajun Chen, Lei Li.
Findings of NAACL 2024. (arXiv:2304.04675, video, code)
kNN-BOX: A Unified Framework for Nearest Neighbor Generation.
Wenhao Zhu, Qianfeng Zhao, Yunzhe Lv, Shujian Huang*, Siheng Zhao, Sizhe Liu, Jiajun Chen.
EACL 2024 System Demonstrations. (arXiv:2302.13574, video, code)
Eliciting the Translation Ability of Large Language Models via Multilingual Finetuning with Translation Instructions.
Jiahuan Li, Hao Zhou, Shujian Huang*, Shanbo Cheng, Jiajun Chen.
TACL 2024. (arXiv:2305.15083, video, code)
2023
Dictionary Definition Augemented Neural Machine Translation for Anciet Chinese Text.
Jiahuan Li, Ruochun Wu, Wenjing Hu, Jixuan Chen, Weilu Xu, Shujian Huang*, Jiajun Chen.
CCMT2023 (in Chinese). Best Paper Award.
IMTLab: An Open-Source Platform for Building, Evaluating, and Diagnosing Interactive Machine Translation Systems.
Xu Huang, Zhirui Zhang, Ruize Gao, Yichao Du, Lemao Liu, Guoping Huang, Shuming Shi, Jiajun Chen, Shujian Huang*.
EMNLP 2023. (code)
Improved Pseudo Data for Machine Translation Quality Estimation with Constrained Beam Search.
Xiang Geng, Yu Zhang, Zhejian Lai, Shuaijie She, Wei Zou, Shimin Tao, Hao Yang, Jiajun Chen, Shujian Huang*.
EMNLP 2023.
Roles of Scaling and Instruction Tuning in Language Perception: Model vs. Human Attention.
Changjiang Gao, Shujian Huang*, Jixing Li, Jiajun Chen.
Findings of EMNLP 2023.
Only 5% Attention Is All You Need: Efficient Long-range Document-level Neural Machine Translation.
Zihan Liu, Zewei Sun, Shanbo Cheng, Shujian Huang, Mingxuan Wang.
IJCNLP-AACL 2023.
Food-500 Cap: A Fine-Grained Food Caption Benchmark for Evaluating Vision-Language Models.
Zheng Ma, Mianzhi Pan, Wenhan Wu, Kanzhi Cheng, Jianbing Zhang*, Shujian Huang*, and Jiajun Chen.
ACM MM 2023.
Extrapolating Large Language Models to Non-English by Aligning Languages.
Wenhao Zhu, Yunzhe Lv, Qingxiu Dong, Fei Yuan, Jingjing Xu, Shujian Huang*, Lingpeng Kong, Jiajun Chen, Lei Li.
arXiv:2308.04948 (video, code)
What Knowledge Is Needed? Towards Explainable Memory for kNN-MT Domain Adaptation.
Wenhao Zhu, Shujian Huang*, Yunzhe Lv, Xin Zheng and Jiajun CHEN.
Findings of ACL 2023. (code)
INK: Injecting kNN Knowledge in Nearest Neighbor Machine Translation.
Wenhao Zhu, Jingjing Xu, Shujian Huang*, Lingpeng Kong and Jiajun CHEN.
ACL 2023. (code)
Local Interpretation of Transformer Based on Linear Decomposition.
Sen Yang, Shujian Huang*, Wei Zou, Jianbing Zhang, Xinyu Dai and Jiajun CHEN.
ACL 2023. (video, code)
BLEURT Has Universal Translations: An Analysis of Automatic Metrics by Minimum Risk Training.
Yiming Yan, Tao Wang, Chengqi Zhao, Shujian Huang*, Jiajun CHEN and Mingxuan Wang.
ACL 2023. (video, code)
Selective Knowledge Distillation for Non-Autoregressive Neural Machine Translation.
Min Liu, Yu Bao, Chengqi Zhao, Shujian Huang*.
AAAI 2023. (code)
CoP: Factual Inconsistency Detection by Controlling the Preference.
Shuaijie She, Xiang Geng, Shujian Huang*, Jiajun Chen.
AAAI 2023. (video, code)
Denoising Pre-Training for Machine Translation Quality Estimation with Curriculum Learning.
Xiang Geng, Yu Zhang, Jiahuan Li, Shujian Huang*, Hao Yang, Shimin Tao, Yimeng Chen, Ning Xie, Jiajun Chen.
AAAI 2023. (video, code)
2022
Better Datastore, Better Translation: Generating Datastores from Pre-Trained Models for Nearest Neural Machine Translation.
Jiahuan Li, Shanbo Cheng, Zewei Sun, Mingxuan Wang, Shujian Huang*.
arXiv:2212.08822.
Unsupervised Paraphrasing via Syntactic Template Sampling.
Yu Bao, Shujian Huang*, Hao Zhou, Lei Li, Xinyu Dai, Jiajun Chen.
SCIENTIA SINICA Informationis 2022. (in Chinese)
Helping the Weak Makes You Strong: Simple Multi-Task Learning Improves Non-Autoregressive Translators,
Xinyou Wang, Zaixiang Zheng*, Shujian Huang*.
EMNLP 2022. (short paper)
FGraDA: A Dataset and Benchmark for Fine-Grained Domain Adaptation in Machine Translation.
Wenhao Zhu, Shujian Huang*, Tong Pu, Pingxuan Huang, Xu Zhang, Jian Yu, Wei Chen, Yanfeng Wang, Jiajun Chen.
LREC 2022.
BiTIIMT: A Bilingual Text-infilling Method for Interactive Machine Translation.
Yanling Xiao, Lemao Liu*, Guoping Huang, Qu Cui, Shujian Huang*, Shuming Shi, Jiajun Chen.
ACL 2022.
latent-GLAT: Glancing at Latent Variables for Parallel Text Generation.
Yu Bao, Hao Zhou, Shujian Huang*, Dongqi Wang, Lihua Qian, Xinyu Dai, Jiajun Chen, Lei Li.
ACL 2022.
Non-Parametric Online Learning from Human Feedback for Neural Machine Translation.
Dongqi Wang, Haoran Wei, Zhirui Zhang, Shujian Huang*, Jun Xie, Jiajun Chen.
AAAI 2022.
2021
Duplex Sequence-to-Sequence Learning for Reversible Machine Translation.
Zaixiang Zheng, Hao Zhou*, Shujian Huang, Jiajun Chen, Jingjing Xu, Lei Li.
NeurIPS 2021.
Learning Kernel-Smoothed Machine Translation with Retrieved Examples.
Qingnan Jiang, Mingxuan Wang, Jun Cao, Shanbo Cheng, Shujian Huang*, Lei Li.
EMNLP 2021.
Non-Parametric Unsupervised Domain Adaptation for Neural Machine Translation.
Xin Zheng, Zhirui Zhang, Shujian Huang*, Boxing Chen, Jun Xie, Weihua Luo, Jiajun Chen.
Findings of EMNLP 2021. (short paper)
Adaptive Nearest Neighbor Machine Translation.
Xin Zheng, Zhirui Zhang, Junliang Guo, Shujian Huang*, Boxing Chen, Weihua Luo, Jiajun Chen.
ACL 2021. (short paper)
When is Char Better Than Subword: A Systematic Study of Segmentation Algorithms for Neural Machine Translation.
Jiahuan Li, Yutong Shen, Shujian Huang*, Xin-Yu Dai, Jiajun Chen.
ACL 2021. (short paper)
Non-Autoregressive Translation by Learning Target Categorical Codes.
Yu Bao, Shujian Huang*, Tong Xiao, Dongqi Wang, Xin-Yu Dai, Jiajun Chen.
NAACL 2021.
DirectQE: Direct Pretraining for Machine Translation Quality Estimation.
Qu Cui, Shujian Huang*, Jiahuan Li, Xiang Geng, Zaixiang Zheng, Guoping Huang, Jiajun Chen.
AAAI 2021.
2020
Toward Making the Most of Context in Neural Machine Translation.
Zaixiang Zheng, Xiang Yue, Shujian Huang*, Jiajun Chen, Alexandra Birch.
IJCAI 2020.
Improving Self-Attention Networks with Sequential Relations.
Zaixiang Zheng, Shujian Huang*, Rongxiang Weng, Xinyu Dai, Jiajun Chen.
IEEE/ACM Transactions on Audio, Speech, and Language Processing 2020.
Mirror-Generative Neural Machine Translation.
Zaixiang Zheng, Hao Zhou, Shujian Huang*, Lei Li, Xin-Yu Dai, Jiajun Chen.
ICLR 2020. (with Highest Ratings from all reviewers, Oral Presentation(selected))
A Reinforced Generation of Adversarial Examples for Neural Machine Translation.
Wei Zou, Shujian Huang*, Jun Xie, Xinyu Dai, Jiajun Chen.
ACL 2020.
Explicit Semantic Decomposition for Definition Generation.
Jiahuan Li, Yu Bao, Shujian Huang*, Xinyu Dai, Jiajun Chen.
ACL 2020.
RPD: A Distance Function Between Word Embeddings.
Xuhui Zhou, Zaixiang Zheng, Shujian Huang.
ACL Student Research Workshop 2020.
GRET: Global Representation Enhanced Transformer.
Rongxiang Weng, Shujian Huang*, Hao-Ran Wei, Heng Yu, Weihua Luo, Lidong Bing, Jiajun Chen.
AAAI 2020.
Generating Diverse Translation by Manipulating Multi-Head Attention.
Zewei Sun, Shujian Huang*, Hao-Ran Wei, Xin-yu Dai, Jiajun Chen.
AAAI 2020.
Acquiring Knowledge from Pre-trained Model to Neural Machine Translation.
Rongxiang Weng, Heng Yu, Shujian Huang*, Shanbo Cheng, Weihua Luo.
AAAI 2020.
2019
Improving Bilingual Lexicon Induction on Distant Language Pairs.
Wenhao Zhu, Zhihao Zhou, Shujian Huang*, Zhenya Lin, Xiangsheng Zhou, Yaofeng Tu, Jiajun Chen.
CCMT 2019. Best English Paper Award
Fine-grained Knowledge Fusion for Sequence Labeling Domain Adaptation.
Huiyun Yang, Shujian Huang*, Xinyu Dai, Jiajun Chen.
EMNLP-IJCNLP 2019.
Dynamic Past and Future for Neural Machine Translation.
Zaixiang Zheng, Shujian Huang*, Zhaopeng Tu, Xin-Yu Dai, Jiajun Chen.
EMNLP-IJCNLP 2019.
Learning Representation Mapping for Relation Detection in Knowledge Base Question Answering.
Peng Wu, Shujian Huang*, Rongxiang Weng, Zaixiang Zheng, Jianbing Zhang, Xiaohui Yan and Jiajun Chen.
ACL 2019.
Generating Sentences from Disentangled Syntactic and Semantic Spaces.
Yu Bao, Hao Zhou, Shujian Huang*, Lei Li, Lili Mou, Olga Vechtomova, XIN-YU DAI and Jiajun CHEN.
ACL 2019.
Utilizing Non-Parallel Text for Style Transfer by Making Partial Comparisons.
Di Yin, Shujian Huang*, Xin-Yu Dai and Jiajun Chen.
IJCAI 2019.
Correct-and-Memorize: Learning to Translate from Interactive Revisions.
Rongxiang Weng, Hao Zhou, Shujian Huang*, Lei Li, Yifan Xia and Jiajun Chen.
IJCAI 2019.
Online Distilling from Checkpoints for Neural Machine Translation.
Hao-Ran Wei, Shujian Huang*, Boxing Chen, Ran Wang, XIN-YU DAI and Jiajun CHEN.
NAACL-HLT 2019.
2018
Modeling Past and Future for Neural Machine Translation.
Zaixiang Zheng, Hao Zhou, Shujian Huang*, Lili Mou, Xinyu Dai, Jiajun Chen, and Zhaopeng Tu.
TACL 2018.
Combining character and word information in neural machine translationusing a multi-level attention.
Huadong Chen, Shujian Huang*, David Chiang, Xinyu Dai, and Jiajun Chen.
NAACL 2018.
Learning to Discriminate Noises for Incorporating External Information in Neural Machine Translation.
Zaixiang Zheng, Shujian Huang*, Zewei Sun, Rongxiang Weng, Xin-Yu Dai, Jiajun Chen.
arXiv:1810.10317, 2018.
Controlling the Transition of Hidden States for Neural Machine Translation.
Zaixiang Zheng, Shujian Huang*, Xin-Yu Dai, Jiajun Chen.
CWMT 2018.
2017
Rgraph:Generating reference graphs for better machine translation evaluation.
Hongjie Ji, Shujian Huang*, Qi Hou, Cunyan Yin, and Jiajun Chen.
CWMT 2017.
Compressing neural networks byapplying frequent item-set mining.
Zi-Yi Dou, Shu-Jian Huang*, and Yi-Fan Su.
ICANN 2017.
Neural Machine Translation with Word Predictions.
Rongxiang Weng, Shujian Huang*, Zaixiang Zheng, Xinyu Dai and Jiajun Chen.
EMNLP 2017.
Top-rank Enhanced Listwise Optimization for Statistical Machine Translation.
Huadong Chen, Shujian Huang*, David Chiang, XIN-YU DAI and Jiajun CHEN.
CoNLL 2017.
AGRA: An Analysis-Generation-Ranking Framework for Automatic Abbreviation from Paper Titles.
Jianbing Zhang, Yixin Sun, Shujian Huang*, Cam-Tu Nguyen, Xiaoliang Wang, Xinyu Dai, Jiajun Chen, Yang Yu.
IJCAI 2017.
Improved Neural Machine Translation with a Syntax-Aware Encoder and Decoder.
Huadong Chen, Shujian Huang*, David Chiang, Jiajun Chen.
ACL 2017.
Chunk-based Bi-Scale Decoder for Neural Machine Translation.
Hao Zhou, Zhaopeng Tu, Shujian Huang, Xiaohua Liu, Hang Li and Jiajun Chen.
ACL 2017. (short paper)
A Neural Probabilistic Structured-Prediction Method for Transition-Based Natural Language Processing.
Hao Zhou, Yue Zhang*, Chuan Chen, Shujian Huang*, Xin-Yu Dai, and Jiajun Chen.
JAIR 2017.
2016
A Search-Based Dynamic Reranking Model for Dependency Parsing.
Hao Zhou, Yue Zhang, Shujian Huang, Junsheng Zhou, XIN-YU DAI and Jiajun Chen.
ACL 2016.
Tree-state based Rule Selection Models for Hierarchical Phrase-based Machine Translation.
Shujian Huang, Huifeng Sun, Chengqi Zhao, Jinsong Su, Xinyu DAI and Jiajun Chen.
IJCAI 2016.
PRIMT: A Pick-Revise Framework for Interactive Machine Translation.
Shanbo Cheng, Shujian Huang*, Huadong Chen, Xinyu DAI and Jiajun Chen.
NAACL-HLT 2016.
Evaluating a Deterministic Shift-Reduce Neural Parser for Constituent Parsing.
Hao Zhou, Yue Zhang, Shujian Huang, Xin-Yu Dai, and Jiajun Chen.
LREC 2016.
Adaptation of Language Models for SMT Using Neural Networks with Topic Information.
Yinggong Zhao, Shujian Huang*, Xinyu Dai, and Jiajun Chen.
ACM TALLIP 2016.
Enhancing Shift-Reduce Constituent Parsing with Action N-Gram Model.
Hao Zhou, Shujian Huang*, Junsheng Zhou, Yue Zhang, Huadong Chen, Xinyu Dai, Chuan Cheng, Jiajun Chen.
ACM TALLIP 2016.
2015
Resolving Coordinate Structures for Chinese Constituent Parsing.
Yichu Zhou, Shujian Huang*, Xinyu Dai, Jiajun Chen.
NLPCC 2015.
Non-linear Learning for Statistical Machine Translation.
Shujian Huang, Huadong Chen, Xinyu Dai, Jiajun Chen.
ACL 2015.
A Neural Probabilistic Structured-Prediction Model for Transition-Based Dependency Parsing.
Hao Zhou, Yue Zhang, Shujian Huang, Jiajun Chen.
ACL 2015.
2014
Learning Word Embeddings from Dependency Relations.
Yinggong Zhao, Shujian Huang, Xinyu Dai, Jianbing Zhang, Jiajun Chen.
IALP 2014.
An Investigation on Statistical Machine Translation with Neural Language Models.
Yinggong Zhao, Shujian Huang, Huadong Chen, and Jiajun Chen.
CCL and NLP-NABD 2014.
2013
Hypothesis Pruning in Learning Word Alignment.
HUANG Shujian, DAI Xinyu, CHEN Jiajun.
Chinese Journal of Electronics 2013.
2012
Enhancing Statistical Machine Translation with Character Alignment.
Ning Xi, Guangchao Tang, Xinyu Dai, Shujian Huang, Jiajun Chen.
ACL 2012. (short paper)
2011
Dealing with Spurious Ambiguity in Learning ITG-based Word Alignment.
Shujian Huang, Stephan Vogel and Jiajun Chen.
ACL 2011. (short paper)
A Syntax-based Pre-reordering Method for Chinese-English Machine Translation.
Qiufeng Wu, Shujian Huang, Xinyu Dai and Jiajun Chen.
CCL 2011. (in Chinese)
2010
Improving Word Alignment by Semi-supervised Ensemble.
Shujian Huang, Kangxi Li, Xinyu Dai and Jiajun Chen.
CoNLL 2010.
2009
Combining ILP and MLN for Coreference Resolution.
Yabing Zhang, Junsheng Zhou, Shujian Huang and Jiajun Chen.
IALP 2009.
Segmenting Long Sentence Pairs for Statistical Machine Translation.
Biping MENG, Shujian Huang, Xinyu Dai and Jiajun Chen.
IALP 2009.
Global Optimization Based On Clustering for Coreference Resolution.
Liu Weipeng, Zhou Junsheng, Huang Shujian and Chen Jiajun.
CCL 2009. (in Chinese)
An Error-Sensitive Metric for Word Alignment in Phrase-based SMT.
Shujian Huang, Ning Xi, Yinggong Zhao, Xinyu Dai, Jiajun Chen.
Journal of Chinese Information Processing 2009. (Revised version of CWMT 2008 paper, in Chinese)
Coreference Resolution using Markov Logic Networks.
Shujian Huang, Yabing Zhang, Junsheng Zhou, Jiajun Chen.
CICLing 2009. Best Poster Award (1/25)
2007
A New Graph Clustering Algorithm for Chinese Noun Phrase Coreference Resolution.
Junsheng Zhou, Shujian Huang, Jiajun Chen and Weiguang Qu.
Journal of Chinese Information Processing 2007. (in Chinese)
Last Update 2024-12-10
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