Pengshan Cai

PhD student at University of Massachusetts, Amherst

profile Amherst, MA
Email: pengshancai@umass.edu
CV
My computing art studio

I study natural language processing, with a specific on natural language generation tasks. My advisors at the UMass is Hong Yu. I am also co-advised by Prof. Fei Liu from Emory University. Prior to UMass, I worked with Yuanzhuo Wang at Institute of computing technology, Chinese Academy of Sciences and Yansong Feng at Peking University on knowledge graph completion.

Apart from research, I like making art works using Python, cooking, writing lyrics and making music.

Experience

  • University of Massachusetts, Amherst. PhD. Amherst, MA, USA, Sep 2017 - Present
  • Tencent AI Lab research intern, Bellevue, WA, USA, May 2022 - Aug 2022
  • IBM Research research intern, Yorktown Heights, NY, USA, May 2021 - Aug 2021
  • Bytedance AI Lab research intern, Mountain View, CA, USA, May 2020 - Aug 2020
  • Siemens Healthineers. research intern, Princeton, NJ, USA, May 2019 - Aug 2019
  • Baidu Inc. research intern, Beijing, China, May 2018 - Aug 2018
  • Institute of Computing Technology, Chinese Academy of Sciences. MS, Beijing, China, Sep 2014 - Jun 2017
  • School of Computer Science, Wuhan University. BS, Wuhan, China, Sep 2010 - Jun 2014

    • Conference & Journal Papers (* equal contribution)

  • PaniniQA: Enhancing Patient Education Through Interactive Question Answering, TACL 2023

      Pengshan Cai*, Zonghai Yao*, Fei Liu, Dakuo Wang, Meghan Reilly, Huixue Zhou, Lingxi Li, Yi Cao, Alok Kapoor, Adarsha Bajracharya, Dan Berlowitz and Hong Yu

  • Generating User-Engaging News Headlines, ACL 2023

      Pengshan Cai, Kaiqiang Song, Sangwoo Cho, Hongwei Wang, Xiaoyang Wang, Hong Yu, Fei Liu and Dong Yu

  • Generation of Patient After-Visit Summaries to Support Physicians, COLING 2022

      Pengshan Cai, Fei Liu, Adarsha Bajracharya, Weisong Liu, Dan Berlowitz, Joe Sills, Alok Kapoor, Richeek Pradhan, David Levy, Hong Yu

  • Learning as Conversation: Dialogue Systems Reinforced for Information Acquisition, NAACL 2022

      Pengshan Cai, Hui Wan, Fei Liu, Mo Yu, Hong Yu, Sachindra Joshi

  • Re2G: Retrieve, Rerank, Generate, NAACL 2022

      Michael Glass, Gaetano Rossiello, Md Faisal Mahbub Chowdhury, Ankita Naik, Pengshan Cai, Alfio Gliozzo

  • Generating Classical Chinese Poems from Vernacular Chinese, EMNLP 2019

      Zhichao Yang*, Pengshan Cai*, Yansong Feng, Fei Li, Weijiang Feng, Elena Suet-Ying Chiu, Hong Yu

  • Path-Based Attention Neural Model for Fine-Grained Entity Typing, AAAI 2018

      Denghui Zhang, Manling Li, Pengshan Cai, Yantao Jia, Yuanzhuo Wang

  • Coarse to Fine: Diffusing Categories in Wikipedia, WWW 2017

      Pengshan Cai, Yansong Feng, Yantao Jia, Yuanzhuo Wang, Xiaolong Jin, Xueqi Cheng

    • Workshop Papers (* equal contribution)

  • Generating Coherent Narratives with Subtopic Planning to Answer How-to Questions, EMNLP Workshops 2022

      Pengshan Cai, Mo Yu, Fei Liu, Hong Yu

  • Learning Knowledge Representation Across Knowledge Graphs, AAAI Workshops 2017

      Pengshan Cai*, Wei Li*, Yansong Feng, Yuanzhuo Wang, Yantao Jia