I am currently a fourth-year Ph.D. student at Arizona State University, advised by Prof. Chitta Baral in the Cognition and Intelligence Lab. I have broad interests in natural language processing. My focus is developig zero-shot learning methods for various NLP tasks, including summarization, commonsense reasoning, question answering, and text classification. Recently, I am working on learning from instructions with LLMs.

Education

B.S. of Computer Science, Worcester Polytechnic Institute, 2014-2018

M.S. of Computer Science, University of Southern California, 2018-2020

Ph.D. of Computer Science, Arizona State University, 2020-2025 (expected)

Publication

Simple Yet Effective Synthetic Dataset Construction for Unsupervised Opinion Summarization
Ming Shen, Jie Ma, Shuai Wang, Yogarshi Vyas, Kalpit Dixit, Miguel Ballesteros, Yassine Benajiba in Findings of EACL 2023

Unsupervised Pronoun Resolution via Masked Noun-Phrase Prediction
Ming Shen*, Pratyay Banerjee*, and Chitta Baral
in Proceedings of ACL-IJCNLP 2021

CommonGen: A Constrained Text Generation Challenge for Generative Commonsense Reasoning
Bill Yuchen Lin*, Wangchunshu Zhou*, Ming Shen, Pei Zhou, Chandra Bhagavatula, Yejin Choi, and Xiang Ren
in Findings of EMNLP 2020

TriggerNER: Learning with Entity Triggers as Explanations for Named Entity Recognition
Bill Yuchen Lin*, Dong-Ho Lee*, Ming Shen, Ryan Moreno, Xiao Huang, Prashant Shiralkar, and Xiang Ren
in Proceedings of ACL-IJCNLP 2020

Methods and Mechanisms for Interactive Novelty Handling in Adversarial Environments
Tung Thai, Ming Shen, Mayank Garg, Ayush Kalani, Nakul Vaidya, Utkarsh Soni, Mudit Verma, Sriram Gopalakrishnan, Chitta Baral, Subbarao Kambhampati, Jivko Sinapov, Matthias Scheutz
in Proceedings of AAMAS 2023

An Architecture for Novelty Handling in a Multi-Agent Stochastic Environment:Case Study in Open-World Monopoly
Tung Thai, Ming Shen, Neeraj Varshney, Sriram Gopalakrishnan, Utkarsh Soni, Matthias Scheutz, Chitta Baral, and Jivko Sinapov
in Proceedings of AAAI 2022 Symposium: Designing Artificial Intelligence for Open Worlds

Experince

May. 2023 - Aug. 2023: Applied Scientist Internship @ Amazon Bedrock

• Project: Multilingual instruction-following with LLMs
• Mentors: Ling Liu and Jie Ma

May. 2022 - Aug. 2022: Applied Scientist Internship @ Amazon Comprehend

• Project: Unsupervised opinion summarization
• Mentors: Jie Ma and Shuai Wang

Aug. 2020 - Present: Graduate Research Associate @ School of Computing and Augmented Intelligence, ASU

• Work as graduate research associate supervised by Dr. Chitta Baral
• Focus on Monopoly and natural language domain under DARPA SAIL-ON program
• Aim to develop systems that quantify and characterize novelties in open-world domains and further react to those novelties.

Nov. 2019 - May 2020: Graduate Student Worker @ Information Science Institute, USC

• Work as graduate student worker supervised by Dr. Xiang Ren
• Focus on LESTAT project under DARPA KAIROS program
• Aim to develop systems that discover event schemas temporally and transmodally for complex events

May 2019 - May. 2020: Research Assistant @ Intelligence and Knowledge Discovery Lab, USC

• Work as research assistant supervised by Dr. Xiang Ren
• Focus on multiple research projects in information extraction and commonsense reasoning domain

Projects

• Demo project for ACL 2019 System Demonstrations paper: AlpacaTag: Active Learning-based Crowd Annotation Framework for Sequence Tagging
  • An open-source web-based data annotation framework for sequence tagging tasks, such as named-entity recognition (NER).
  • Dynamically provides the most informative unlabeled instance with suggested tagging for users to label with a back-end active learned model.

Awards And Honors

2020 - Present: University Doctoral Fellowship, Arizona State University
2020: CIDSE Doctoral Fellowship, Arizona State University

SERVICES

Reviewer: ACL Rolling Review, COLING, ACL, EMNLP