Jiangjie Chen

Ph.D. Candidate

Fudan University

Biography

Jiangjie Chen (陈江捷) is a third-year Ph.D. candidate at Fudan University (FDU) in School of Computer Science, Shanghai, China, where he is advised by Prof. Yanghua Xiao at Knowledge Works Lab. He is also currently a research intern at ByteDance AI Lab, where he works closely with Prof. Lei Li (now at UCSB), Dr. Hao Zhou (now at Tsinghua University) and Dr. Changzhi Sun.

He is a zealous believer in reasoning over natural language and dedicated to make neural models right for the right reasons. His research interests mainly lie in Text Reasoning, Text Generation and Explainable NLP, and particularly the intersection of them. His previous research experiences also include Knowledge Graph Construction.

( Download my resumé. Could be outdated. 😶)

Interests

Text Reasoning
Text Generation
Knowledge Acquisition and Application
Mountaineering 🧗‍♂️
Tennis 🎾 (3.0)

Education

Ph.D. in CS, 2019 - 2024 (estimated)

Fudan University
B.S. in CS (with honor), 2014 - 2019

Fudan University

News

[4/27/2022] E-KAR will be presented at the Commonsense Representation and Reasoning (CSRR) workshop @ ACL 2022, discussions welcomed!
[4/25/2022] E-KAR will be presented at ACL 2022 (virtually) in a poster session, welcome to check it out!
[4/8/2022] Our paper (ACT) got accepted at NAACL-HLT 2022!
[3/26/2022] The leaderboard of E-KAR has been released at EvalAI! Welcome to participate!
[3/19/2022] Our work LOREN received the attention of WikiResearch Team 🧐, here’s the tweet.
[2/25/2022 ~ 2/28/2022] Giving oral & poster presentations about LOREN and EDUCAT at AAAI 2022 virtual conference.
[2/24/2022] Our paper (E-KAR) got accepted at ACL 2022 (Findings)!

Experience

Research Intern

ByteDance AI Lab

Nov 2019 – Present Shanghai

Knowledge-guided text generation and natural language reasoning.

Student Researcher

Knowledge Works Lab (KW, 知识工场) at Fudan University

Apr 2017 – Present Shanghai

Knowledge graph, text generation and reasoning.

Research Themes

Theme I - Explainable Text Reasoning, Being Right for the Right Reasons 🤔

For humans, intuitive inferences are made every now and then. However, it would require reasons for humans to convince others and justify themselves of their inferences or decisions. How can machines better convince humans of their predictions? The key may lie in being right for the right and faithful reasons.

Feb 27, 2022

Theme II - Towards Factual, Controllable and Versatile Text Generation 🤖

The success of deep text generation is being held back by its non-factuality. How to unleash the power of text generation models while restraining them from talking gibberish? Perhaps the first step is the identification of non-factuality.

Feb 27, 2022

Featured Publications

Jiangjie Chen, Rui Xu, Ziquan Fu, Wei Shi, Zhongqiao Li, Xinbo Zhang, Changzhi Sun, Lei Li, Yanghua Xiao, Hao Zhou

February, 2022 In The 60th Annual Meeting of the Association for Computational Linguistics (ACL 2022) - Findings

E-KAR: A Benchmark for Rationalizing Natural Language Analogical Reasoning

We benchmark knowledge-intensive analogical reasoning with human-annotated explanations.

Jiangjie Chen, Qiaoben Bao, Changzhi Sun, Xinbo Zhang, Jiaze Chen, Hao Zhou, Yanghua Xiao, Lei Li

February, 2022 In The 36th AAAI Conference on Artificial Intelligence (AAAI 2022) (oral)

LOREN: Logic-Regularized Reasoning for Interpretable Fact Verification

Interpretable fact verification with phrasal decomposition and logic regularization.

Jiangjie Chen, Chun Gan, Sijie Cheng, Hao Zhou, Yanghua Xiao, Lei Li

February, 2022 In The 36th AAAI Conference on Artificial Intelligence (AAAI 2022) (oral)

Unsupervised Editing for Counterfactual Stories

Creating counterfactual story endings (what-if stories) with unsupervised editing.

Recent Publications

Quickly discover relevant content by filtering publications.

Chun Zeng, Jiangjie Chen, Tianyi Zhuang, Rui Xu, Hao Yang, Ying Qin, Shimin Tao, Yanghua Xiao (2022). Neighbors Are Not Strangers: Improving Non-Autoregressive Translation under Low-Frequency Lexical Constraints. In The 2022 Conference of the North American Chapter of the Association for Computational Linguistics - Human Language Technologies (NAACL-HLT 2022).

PDF Cite Code

Jiangjie Chen, Rui Xu, Ziquan Fu, Wei Shi, Zhongqiao Li, Xinbo Zhang, Changzhi Sun, Lei Li, Yanghua Xiao, Hao Zhou (2022). E-KAR: A Benchmark for Rationalizing Natural Language Analogical Reasoning. In The 60th Annual Meeting of the Association for Computational Linguistics (ACL 2022) - Findings.

PDF Cite Project Poster Slides Video

Shineng Fang, Jiangjie Chen, Xinyao Shen, Yunwen Chen, Yanghua Xiao (2022). FalCon: A Faithful Contrastive Framework for Response Generation in TableQA Systems. In The 27th International Conference on Database Systems for Advanced Applications (DASFAA 2022).

PDF Cite Code

Jiangjie Chen, Qiaoben Bao, Changzhi Sun, Xinbo Zhang, Jiaze Chen, Hao Zhou, Yanghua Xiao, Lei Li (2022). LOREN: Logic-Regularized Reasoning for Interpretable Fact Verification. In The 36th AAAI Conference on Artificial Intelligence (AAAI 2022) (oral).

PDF Cite Code Poster Slides Video Demo

Jiangjie Chen, Chun Gan, Sijie Cheng, Hao Zhou, Yanghua Xiao, Lei Li (2022). Unsupervised Editing for Counterfactual Stories. In The 36th AAAI Conference on Artificial Intelligence (AAAI 2022) (oral).

PDF Cite Code Poster Slides Video

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