I am currently a second-year Ph.D. student at Uninversity of Southern California, advised by Prof. Xiang Ren.

Generally, my research interests are Natural Language Processing and Machine Learning. I have been working on continual learning, robustness&fairness, and interpretation techniques of neural network predictions.


  • Apr. 2021: We release a new preprint studying Lifelong Learning of Few-shot Learners across NLP Tasks!

  • Apr. 2021: Our paper On Transferability of Bias Mitigation Effects in Language Model Fine-Tuning got accepted at NAACL 2021. It is also my internship project at Snap Inc!

  • Sep. 2020: Our paper Visually Grounded Continual Learning of Compositional Phrases got accepted at EMNLP 2020.

  • Aug. 2020: Finished my 3-month internship at Snapchat!

  • Jul. 2020: Two papers accepted at Lifelong Learning workshop@ICML 2020 and Continual Learning workshop@ICML 2020. We studied a task-free continual learning algorithm, and proposed a task setup for visually grounded continual compostional phrase learning.

  • Apr. 2020: Our paper about reducing unintended bias in hate speech classifiers by regularizing post-hoc explanations was accepted at ACL 2020.

  • Dec. 2019: Our paper discussing explanation algorithms for compositional semantics captured in neural sequence models got spotlighted at ICLR 2020.


  1. Learn Continually, Generalize Rapidly: Lifelong Knowledge Accumulation for Few-shot Learning. Xisen Jin, Bill Yuchen Lin, Mohammad Rostami, Xiang Ren. Arxiv


  1. On Transferability of Bias Mitigation Effects in Language Model Fine-Tuning. Xisen Jin, Francesco Barbieri, Brendan Kennedy, Aida Mostafazadeh Davani, Leonardo Neves, Xiang Ren. NAACL 2021 [code&data]

  2. Visually Grounded Continual Learning of Compositional Phrases. Xisen Jin, Junyi Du, Arka Sadhu, Ram Nevatia and Xiang Ren. EMNLP 2020 [code&data] [project page]

  3. Gradient Based Memory Editing for Task-Free Continual Learning. Xisen Jin, Junyi Du, Xiang Ren. Lifelong ML@ICML 2020. [code]

  4. Contextualizing Hate Speech Classifiers with Post-hoc Explanation. Brendan Kennedy*, Xisen Jin*, Aida Mostafazadeh Davani, Morteza Dehghani and Xiang Ren. ACL 2020 short paper. [project page] [code]

  5. Towards Hierarchical Importance Attribution: Explaining Compositional Semantics for Neural Sequence Models. Xisen Jin, Zhongyu Wei, Junyi Du, Xiangyang Xue and Xiang Ren. ICLR 2020 spotlight. [project page] [code]

  6. Explicit State Tracking with Semi-Supervision for Neural Dialogue Generation. Xisen Jin, Wenqiang Lei, Zhaochun Ren, Hongshen Chen, Shangsong Liang, Yihong Eric Zhao and Dawei Yin. CIKM 2018 full Paper. [code] [slides (pdf)] [slides (pptx)]

  7. Sequicity: Simplifying Task-oriented Dialogue Systems with Single Sequence-to-Sequence Architectures. Wenqiang Lei, Xisen Jin, Min-Yen Kan, Zhaochun Ren, Xiangnan He and Dawei Yin. ACL 2018 long paper. [code]


University of Southern California, 2019.8 -

Fudan University, 2015.9 - 2019.7

National University of Singapore Exchange, 2017.8 - 2017.12

Research & Interns

Intelligence and Knowledge Discovery (INK) Research Lab

Snap Inc.

Natural Language Processing Group, School of Data Science

Web Information Retrieval / Natural Language Processing Group (WING), National University of Singapore

Data Science Lab, JD.com, Beijing, China

Mircosoft Research Asia, Beijing, China

  • Research Intern, Natural Language Computing group. From Jul. 2018 to Oct. 2018
  • Advisor: Dr. Nan Duan, Dr. Ming Zhou

Details of research projects in CV