
Ph.D. at Max Planck Institute for Intelligent Systems, Tübingen, Germany (2020-now)
📭 Email: zhijing.jin@connect.hku.hk
📁 Google Scholar / 👩🎓 CV
I am an enthusiastic NLP researcher and effective altruist. I am a PhD in NLP and Causality with Bernhard Schoelkopf at Max Planck Institute, Tuebingen, Germany, and also a research scientist intern with Amazon AI supervised by Prof Zheng Zhang. I am in the meantime mentored by Prof Rada Mihalcea from University of Michigan, and Prof Mrinmaya Sachan at ETH. My dream is to be a professor and actively promote AI for social good. To this end, I am organizing the 1st workshop of NLP for Positive Impact at ACL 2021, and 1st workshop on RobustAI at ICLR 2021. I am also engaged in Effective Altruism, a social movement to involve people in doing good with high efficiency. Previously, I obtained my bachelor’s degree (1st Class Honors) from the University of Hong Kong. [More info]
Here is a list of topics I work on:
- Text Generation TextGen: Text style transfer; KG-to-text generation; adversarial generation (for NLP robustness Robust).
- Information Extraction IE: Relation Extraction (RE); Named Entity Recognition (NER).
- Medical AI Medical: NER on clinical notes; clinical outcome prediction.
- Causality & Language: Two ongoing projects in this promising virgin field.
- I also have a growing interest in philosophy, epistemology, and how to improve the political system. Feel free to contact me for interdisciplinary research.
News
- Dec 27, 2020: I will present our EMNLP 2020 paper ABSA robustness at CSSNLP seminar.
- Dec 18, 2020: I presented two papers at the INLG 2020 workshop, WebNLG+.
- Dec 12, 2020: Our RobustAI workshop is accepted to ICLR 2021!
- Dec 6-11, 2020: I am attending NeurIPS, and COLING. Happy to grab a chat!
- Nov 21, 2020: We achieved the 1st place at the INLG 2020 workshop, WebNLG+. Plus, our second paper, CycleGT, is admitted to the workshop too.
- Nov 17, 2020: Our ABSA robustness paper is presented at EMNLP 2020!
- Nov 7, 2020: Our 1st workshop on NLP for Positive Impact is accepted to ACL@2021!
- Sept 30, 2020: 1 paper accepted to COLING 2020: GenWiki, an unsupervised graph-to-text dataset with 1.3M data.
- For more news, please check here.
Publications
For the .bib file of my publications, please check here.

Robust Tasty Burgers, Soggy Fries: Probing Aspect Robustness in Aspect-Based Sentiment Analysis
Xiaoyu Xing*, Zhijing Jin*, Di Jin, Bingning Wang, Qi Zhang, Xuanjing Huang
EMNLP 2020 / Paper / Code / Slides

TextGen IE GenWiki: A Dataset of 1.3 Million Content-Sharing Text and Graphs for
Unsupervised Graph-to-Text Generation
Zhijing Jin*, Qipeng Guo*, Xipeng Qiu, Zheng Zhang
COLING 2020 / Paper / Poster / Code

TextGen P2: A Plan-and-Pretrain Approach for Knowledge Graph-to-Text Generation
Qipeng Guo, Zhijing Jin, Ning Dai, Xipeng Qiu, Xiangyang Xue, David Wipf, Zheng Zhang
INLG 2020 Workshop / Paper / Code
Top #1 in the Leaderboard of WebNLG+

TextGen IE CycleGT: Unsupervised Graph-to-Text and Text-to-Graph Generation via Cycle Training
Qipeng Guo*, Zhijing Jin*, Xipeng Qiu, Weinan Zhang, David Wipf, Zheng Zhang
INLG 2020 Workshop (Oral) / Paper / Code

TextGen IE Fork or Fail: Cycle-Consistent Training with Many-to-One Mappings
Qipeng Guo, Zhijing Jin, Ziyu Wang, Xipeng Qiu, Weinan Zhang, Jun Zhu, Zheng Zhang, David Wipf
arXiv 2020 / Paper / Code

TextGen Deep Learning for Text Style Transfer: A Survey
Di Jin*, Zhijing Jin*, Zhiting Hu, Olga Vechtomova, Rada Mihalcea
arXiv 2020 / Paper

IE Relation of the Relations: A New Paradigm of the Relation Extraction Problem
Zhijing Jin*, Yongyi Yang*, Xipeng Qiu, Zheng Zhang
EMNLP 2020 (later withdrawn) / Paper / Code

TextGen Hooks in the Headline: Learning to Generate Headlines with Controlled Styles
Di Jin, Zhijing Jin, Tianyi Joey Zhou, Lisa Orii, Peter Szolovits
ACL 2020 Talk / Paper / Code / Slides

TextGen A Simple Baseline to Semi-Supervised Domain Adaptation for Machine Translation
Di Jin, Zhijing Jin, Tianyi Joey Zhou, Peter Szolovits
arXiv 2020 / Paper / Code

Robust Is BERT Really Robust? A Strong Baseline for Natural Language Attack on Text Classification and Entailment
Di Jin*, Zhijing Jin*, Tianyi Joey Zhou, Peter Szolovits
AAAI 2020 (20.6%) / Paper / Code / Slides / Poster / MIT News / ACM TechNews / WeVolver / VentureBeat / Synced (Chinese)
Oral Presentation


Medical Deep Natural Language Processing to Identify Symptom Documentation in Clinical Notes for Patients with Heart Failure Undergoing Cardiac Resynchronization Therapy (CRT)
Richard Leiter*, Enrico Santus*, Zhijing Jin, Katherine Lee, …, Charlotta Lindvall
AAHPM 2020 / Paper / Code

TextGen IMaT: Unsupervised Text Attribute Transfer via Iterative Matching and Translation
Zhijing Jin*, Di Jin*, Jonas Mueller, Nicholas Matthews, Enrico Santus
EMNLP 2019 / Paper / Code / Poster

IE GraphIE: A Graph-Based Framework for Information Extraction
Yujie Qian, Enrico Santos, Zhijing Jin, Jiang Guo, Regina Barzilay
NAACL 2019 / Paper / Code

Tool 3D Traffic Simulation for Autonomous Vehicles in Unity and Python
Zhijing Jin, Tristan Swedish, Ramesh Raskar
arXiv 2018 / Paper / Code

CogSci Prediction of Story Ending with Optimistic and Pessimistic Mindsets
Zhijing Jin, Prof. Patrick Winston (1943-2019)

Tool Word Representations for Computing Semantic Relatedness
Zhijing Jin, Xiaolong Gong, Linpeng Huang
In contribution to the AAAI 2018 paper.
Tutorial & Survey
NLP Graph Neural Net Applications for Natural Language Processing
Xipeng Qiu, Zhijing Jin, Xiangkun Hu
Paper 2020