I am currently an applied scientist at AWS AI Labs. I obtained Ph.D. degree from the Language Analysis group of SCIR lab at Harbin Institute of Technology, under the supervision of Dr. Haifeng Wang and Prof. Wanxiang Che.
From 2014 to 2015, I was a joint Ph.D. student at CLSP in Johns Hopkins University supervised by Prof. David Yarowsky.
Prior to joining AWS, I was a postdoc researcher at MIT CSAIL working with Prof. Regina Barzilay. I was a member of the Natural Language Processing group, and also part of the MLPDS Consortium.
My research interests span a wide range of areas in natural language processing and machine learning. My earlier research has focused on low-resource learning with applications in cross-lingual, task, and domain transfer (ACL15, JAIR16, EMNLP18, EMNLP19a, EMNLP19b), as well as interdisciplinary applications in chemical sciences (JCIM21, JCIM23a, JCIM23b). Recently I have been mostly working on various topics and industrial applications of large language models (LLMs), including Text2SQL (Amazon Q in QuickSight), RAG (Knowledge Bases for Amazon Bedrock), Knowledge Editing (ACL24), and LLM Customization.
Prior to joining AWS, I was a postdoc researcher at MIT CSAIL working with Prof. Regina Barzilay. I was a member of the Natural Language Processing group, and also part of the MLPDS Consortium.
My research interests span a wide range of areas in natural language processing and machine learning. My earlier research has focused on low-resource learning with applications in cross-lingual, task, and domain transfer (ACL15, JAIR16, EMNLP18, EMNLP19a, EMNLP19b), as well as interdisciplinary applications in chemical sciences (JCIM21, JCIM23a, JCIM23b). Recently I have been mostly working on various topics and industrial applications of large language models (LLMs), including Text2SQL (Amazon Q in QuickSight), RAG (Knowledge Bases for Amazon Bedrock), Knowledge Editing (ACL24), and LLM Customization.
Selected Papers [Google Scholar]
* indicates authors with equal contribution.
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Propagation and Pitfalls: Reasoning-based Assessment of Knowledge Editing through Counterfactual Tasks.
Wenyue Hua*, Jiang Guo*, Mingwen Dong, Henghui Zhu, Patrick Ng, Zhiguo Wang
ACL Findings, 2024
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RxnScribe: A Sequence Generation Model for Reaction Diagram Parsing.
Yujie Qian, Jiang Guo, Zhengkai Tu, Connor W. Coley and Regina Barzilay
JCIM, 2023
[Code & Data] [Demo] -
MolScribe: Robust Molecular Structure Recognition with Image-to-Graph Generation.
Yujie Qian, Jiang Guo, Zhengkai Tu, Zhening Li, Connor W. Coley and Regina Barzilay
JCIM, 2023
[Code & Data] [Demo] -
Automated Chemical Reaction Extraction from Scientific Literature.
Jiang Guo*, A. Santiago Ibanez-Lopez*, Hanyu Gao, Victor Quach, Connor W. Coley, Klavs F. Jensen and Regina Barzilay
JCIM, 2021
[Code & Data] [ChemBERT at HuggingFace] -
Evaluating and Clustering Retrosynthesis Pathways with Learned Strategy.
Yiming Mo, Yanfei Guan, Pritha Verma, Jiang Guo, Mike E. Fortunato, Zhaohong Lu, Connor W. Coley and Klavs F. Jensen
Chemical Science, 2021
[Code] -
Curriculum CycleGAN for Textual Sentiment Domain Adaptation with Multiple Sources.
Sicheng Zhao*, Yang Xiao*, Jiang Guo*, Xiangyu Yue*, Jufeng Yang, Ravi Krishna, Pengfei Xu and Kurt Keutzer
The Web Conference, 2021
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Working Hard or Hardly Working: Challenges of Integrating Typology into Neural Dependency Parsers.
Adam Fisch*, Jiang Guo* and Regina Barzilay
EMNLP, 2019
[Code] -
Cross-Lingual BERT Transformation for Zero-Shot Dependency Parsing.
Yuxuan Wang‡, Wanxiang Che, Jiang Guo, Yijia Liu and Ting Liu
EMNLP, 2019
[Code] -
GraphIE: A Graph-Based Framework for Information Extraction.
Yujie Qian‡, Enrico Santus, Zhijing Jin‡, Jiang Guo and Regina Barzilay
NAACL, 2019
[Code] -
Multi-Source Domain Adaptation with Mixture of Experts.
Jiang Guo, Darsh J Shah‡ and Regina Barzilay
EMNLP, 2018
[Code] -
A Neural Transition-based Approach for Semantic Dependency Graph Parsing.
Yuxuan Wang‡, Wanxiang Che, Jiang Guo and Ting Liu
AAAI, 2018
[Code] -
The HIT-SCIR System for End-to-End Parsing of Universal Dependencies.
Wanxiang Che, Jiang Guo, Yuxuan Wang, Bo Zheng, Huaipeng Zhao, Yang Liu, Dechuan Teng and Ting Liu
CoNLL 2017 (shared task, ranked 4/33)
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Effective Deep Memory Networks for Distant Supervised Relation Extraction.
Xiaocheng Feng, Jiang Guo, Bing Qin, Ting Liu
IJCAI, 2017
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A General Framework for Content-enhanced Network Representation Learning.
Xiaofei Sun‡, Jiang Guo, Xiao Ding, Ting Liu
arXiv, 2016
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A Unified Architecture for Semantic Role Labeling and Relation Classification.
Jiang Guo, Wanxiang Che, Haifeng Wang, Ting Liu, Jun Xu
COLING, 2016
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A Universal Framework for Inductive Transfer Parsing across Multi-typed Treebanks.
Jiang Guo, Wanxiang Che, Haifeng Wang, Ting Liu
COLING, 2016
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Exploring Segment Representations for Neural Segmentation Models.
Yijia Liu, Wanxiang Che, Jiang Guo, Bing Qin, Ting Liu
IJCAI, 2016
[Code] -
A Distributed Representation-based Framework for Cross-lingual Transfer Parsing.
Jiang Guo, Wanxiang Che, David Yarowsky, Haifeng Wang, Ting Liu
JAIR, 2016
[Code] -
A Representation Learning Framework for Multi-Source Transfer Parsing.
Jiang Guo, Wanxiang Che, David Yarowsky, Haifeng Wang, Ting Liu
AAAI, 2016
[Code] [Data] -
Cross-lingual Dependency Parsing Based on Distributed Representations.
Jiang Guo, Wanxiang Che, David Yarowsky, Haifeng Wang, Ting Liu
ACL, 2015
[Code] -
Learning Semantic Hierarchies: A Continuous Vector Space Approach.
Ruiji Fu*, Jiang Guo*, Bing Qin, Wanxiang Che, Haifeng Wang, Ting Liu
TASLP, 2015
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Revisiting Embedding Features for Simple Semi-supervised Learning.
Jiang Guo, Wanxiang Che, Haifeng Wang, Ting Liu
EMNLP, 2014
[Code] -
Learning Sense-specific Word Embeddings By Exploiting Bilingual Resources.
Jiang Guo, Wanxiang Che, Haifeng Wang, Ting Liu
COLING, 2014
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Learning Semantic Hierarchies via Word Embeddings.
Ruiji Fu, Jiang Guo, Bing Qin, Wanxiang Che, Haifeng Wang, Ting Liu
ACL, 2014
[Data: Dev, Test, Readme]
Book and Translation:
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Natural Language Processing: A Pre-trained Model Approach.
Wanxiang Che, Jiang Guo, Yiming Cui
Publishing House of Electronics Industry, 2021.07
[Code & Slides] -
Neural Network Methods for Natural Language Processing.
Yoav Goldberg (Author). Wanxiang Che, Jiang Guo, Weinan Zhang, Ming Liu (Translators)
China Machine Press, 2018.05
Academic Services
- Senior PC: AAAI (2021, 2022)
- Area Chair: CCL (2019, 2020), COLING (2022)
- Journal Reviewer: IEEE/ACM TASLP, ACM TIST, ACS JCIM
- Conference Reviewer: EMNLP, NAACL, ACL, NLPCC, COLM
- PC Member: Student Research Workshop of ACL (2016, 2017, 2018), NAACL (2017, 2018)
- PC Member: NAACL 2016 Workshop on Multilingual and Crosslingual Methods in NLP
- Reviewing Coordinator: ACL (2014), EMNLP (2014), NAACL (2015)
Miscellaneous
- How to Write a Good Paper and How to Give a Good Talk by Liang Huang
- "Knowing is not enough, we must apply. Willing is not enough, we must do." -- Johann Wolfgang von Goethe