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PhD at Max Planck Institute & ETH, affiliated at UMich (2020-2024 expected)
Email: jinzhi@umich.edu (This is a Gmail account)
👩‍🎓Google Scholar / 📁CV / twitter-icon@ZhijingJin

I am an enthusiastic AI researcher and social good promoter. I am currently a 2nd-year PhD (started in 2020) supervised by Prof Bernhard Schoelkopf at Max Planck Institute & ETH, mentored by Prof Rada Mihalcea (UMich), and co-supervised through the ELLIS PhD Program by Prof Mrinmaya Sachan and Prof Ryan Cotterell at ETH.

My research has two goals: (1) to promote NLP for social good, and (2) to improve AI by connecting NLP with causality. And my career goal is to be a professor in NLP. (Quick pointers: my bio, mentors & mentees, and publications.)

Highlights

Publications

To follow talks on my research, please check out my YouTube. For the .bib file of my publications, please check here.

Logical Fallacy Detection
Zhijing Jin*, Abhinav Lalwani*, Tejas Vaidhya, Xiaoyu Shen, Yiwen Ding, Zhiheng Lyu, Mrinmaya Sachan, Rada Mihalcea, Bernhard Schölkopf
arXiv 2022 / Paper / Code

Slangvolution: A Causal Analysis of Semantic Change and Frequency Dynamics in Slang
Daphna Keidar*, Andreas Opedal*, Zhijing Jin, Mrinmaya Sachan
ACL 2022 / Paper / Slides

Independent Causal Mechanisms for NLP

Causal Direction of Data Collection Matters: Implications of Causal and Anticausal Learning for NLP
Zhijing Jin*, Julius von Kügelgen*, Jingwei Ni, Tejas Vaidhya, Ayush Kaushal, Mrinmaya Sachan, Bernhard Schölkopf
EMNLP 2021 (Oral) / Paper / Code / Poster / Slides / Talk

Causation Between COVID Twitter Sentiments and Policies

Mining the Cause of Political Decision-Making from Social Media: A Case Study of COVID-19 Policies across the US States
Zhijing Jin, Zeyu Peng, Tejas Vaidhya, Bernhard Schoelkopf, Rada Mihalcea
Findings of EMNLP 2021 / Paper / Code / Poster / Slides / Talk

How Good Is NLP? A Sober Look at NLP Tasks through the Lens of Social Impact
Zhijing Jin, Geeticka Chauhan, Brian Tse, Mrinmaya Sachan, Rada Mihalcea
Findings of ACL 2021 / Paper / Code / Poster / Slides / Talk
Invited Talk at CyberValley, Germany

TextGen Deep Learning for Text Style Transfer: A Survey
Di Jin*, Zhijing Jin*, Zhiting Hu, Olga Vechtomova, Rada Mihalcea
CL Journal 2022 / Paper / Slides

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 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
AISTATS 2021 / Paper / Poster / Code

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 2020

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

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 / Paper / Code / Slides / Talk

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 An Artificial Intelligence Algorithm to Identify Documented Symptoms in Patients with Heart Failure who Received Cardiac Resynchronization Therapy
Richard Leiter, Enrico Santus, Zhijing Jin, Katherine Lee, …, Charlotta Lindvall
JPSM 2020 / Article / Code

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