Current Research Overview
- Promote NLP for Social Good [Reading List] (5+ papers, 3 workshops)
- Position paper “How Good Is NLP?“@ACL 2021 Findings & my curated reading list
- NLP to analyze COVID policies (EMNLP 2021 Findings)
- NLP for climate change (2021 paper)
- NLP for policymaking [Book chapter] (2021)
- NLP Alignment for AI safety (2021), learning moral rules for AI (CogSci Symposium, 2022), moral exceptions (NeurIPS 2022 Oral)
- NLP for healthcare (AAHPM 2020, JPSM 2020)
- Organization: I organize NLP4SG Initiative, the yearly NLP for Positive Impact Workshop (with ACL 2021, with EMNLP 2022)
- Talk: “What is NLP for Social Good”@NLP for Positive Impact Workshop (video, slides)
- Connect NLP & Causality [Reading List] (6+ papers, 1 conference, 1 tutorial, 1 workshop)
- Causality within NLP tasks (Independent Causal Mechanism for NLP@EMNLP 2021 oral, Slangvolution@ACL 2022, translationese@NAACL 2022, causality for fairness – ongoing)
- Causality for decision-making (policy causal analysis@EMNLP 2021 Findings, AI Scholar project – ongoing)
- Logical fallacy detection & misinformation (paper 2021)
- NLP for causal discovery (ongoing)
- Organization: I organize the 1st CausalNLP Tutorial (EMNLP 2022) and RobustML Workshop (ICLR 2021), and I am the Publications Chair of the 1st conference on Causal Learning and Reasoning (CLeaR) 2022.
- Talk: CausalNLP Tutorial (video, slides for Part1, slides for Part 2, PDF)
- Establish a global supportive network for NLP researchers
- Organization: I organize the ACL Year-Round Mentorship (a network of 650+ mentees and 90+ NLP mentors)
- Resources: My list of useful resources for career advice in NLP/AI. [Other resources]
- “My PhD Journey”@SSLL Workshop (my slides)
Pre-PhD Research Overview
Before starting my PhD (from undergrad to 2020), I spent huge efforts to get familiarized with many subtasks of NLP, including
Text Generation TextGen (11 papers): 6 papers on Graph-to-text generation; 3 papers on text style transfer (EMNLP 2019, ACL 2020, CL Journal 2021 survey); 2 papers on adversarial text generation (for NLP robustness Robust; AAAI 2020 oral, EMNLP 2020).
Information Extraction IE (7 papers): 4 papers on Relation Extraction (RE) (EMNLP 2020, AISTATS 2021, COLING 2020, arXiv 2021), 3 papers on Named Entity Recognition (NER) (NAACL 2019, Medical JPSM 2020, AAHPM 2020).
Complete List of Publications
To follow talks on my research, please check out my YouTube. For the .bib of my publications, please import this .bib file to your overleaf.
When to Make Exceptions: Exploring Language Models as Accounts of Human Moral Judgment
Zhijing Jin*, Sydney Levine*, Fernando Gonzalez*, Ojasv Kamal, Maarten Sap, Mrinmaya Sachan†, Rada Mihalcea†, Josh Tenenbaum†, Bernhard Schoelkopf†
NeurIPS 2022 (Oral) / CogSci 2022 (Disciplinary Diversity and Integration Award) / Paper / Code / Slides / 5-Min Talk@NeurIPS / Twitter Thread / Invited Talk@CyberValley, Germany
How Is NLP Addressing the UN Sustainable Development Goals? A Challenge Set to Analyze NLP for Social Good Papers
Fernando Gonzalez*, Zhijing Jin*, Jad Beydoun, Bernhard Schölkopf, Tom Hope, Mrinmaya Sachan†, Rada Mihalcea†
2022 / Paper / Code / Slides
Invited Talk at AI+X Summit at ETH
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 / Tweet
MIT News article
Invited Talk at CyberValley, Germany
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 / 7-Min Video
Differentially Private Language Models for Secure Data Sharing
Justus Mattern, Zhijing Jin, Benjamin Weggenmann, Mrinmaya Sachan, Bernhard Schoelkopf
EMNLP 2022 / Paper
Original or Translated? A Causal Analysis of the Impact of Translationese on Machine Translation Performance
Jingwei Ni*, Zhijing Jin*, Markus Freitag, Mrinmaya Sachan, Bernhard Schölkopf
NAACL 2022 (Oral) / Paper / Code / Slides / Twitter Thread / 13-Min Video
State-of-the-art generalisation research in NLP: a taxonomy and review
Dieuwke Hupkes, Mario Giulianelli, Verna Dankers, Mikel Artetxe, Yanai Elazar, Tiago Pimentel, …, Ryan Cotterell, Zhijing Jin
arXiv 2022 / Paper
Can Large Language Models Distinguish Cause from Effect?
Zhiheng LYU*, Zhijing Jin*, Rada Mihalcea, Mrinmaya Sachan, Bernhard Schölkopf
UAI 2022 Causal Representation Learning Workshop / Paper / Code / Poster
Natural Language Processing for Policymaking
Zhijing Jin, Rada Mihalcea
Book Chapter of Handbook of Computational Social Science for Policy 2022 (European Commission Joint Research Center)
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 / 12-Min Video / Twitter Thread
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 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.
Survey
NLP Graph Neural Net Applications for Natural Language Processing
Xipeng Qiu, Zhijing Jin, Xiangkun Hu
Paper 2020