Pei (Patrick) Chen

Ph.D. in Computer Science

Texas A&M University

Welcome!

I am a Ph.D. in Computer Science graduated from the TAMU NLP group, Department of Computer Science and Engineering at Texas A&M University. I enjoy doing research in the fields of Natural Language Processing, Deep Learning and applying deep learning models to practical NLP problems and applications. I joined Amazon.com as an Applied Scientist since Jan, 2024.

Email: chenpei.net@gmail.com
Links: GitHub LinkedIn Google Scholar

Interests

Large Language Models
Information Extraction

Education

Ph.D. in Computer Science, 2019 - 2024

Texas A&M University
MS in Finance, 2016 - 2018

Southwestern University of Finance and Economics
B.Eng. in Simulation Engineering, 2010 - 2014

National University of Defense Technology

News

May/24 One paper accepted to NAACL-2024 and one accepted to ACL-2024. ✨
Sep/23 One paper accepted to NeurIPS-2023 as a spotlight. 👋

Selected Publications

Pei (Patrick) Chen, Boran Han, Shuai Zhang (2024). CoMM: Collaborative Multi-Agent, Multi-Reasoning-Path Prompting for Complex Problem Solving.

Cite arXiv

Wangtao Sun, Haotian Xu, Xuanqing Yu, Pei (Patrick) Chen, Shizhu He, Jun Zhao, Kang Liu (2024). ItD: Large Language Models Can Teach Themselves Induction through Deduction.

Cite arXiv

Ming Li, Pei (Patrick) Chen, Chenguang Wang, Hongyu Zhao, Yijun Liang, Yupeng Hou, Fuxiao Liu, Tianyi Zhou (2024). Mosaic IT: Enhancing Instruction Tuning with Data Mosaics.

Cite arXiv

Pei (Patrick) Chen, Soumajyoti Sarkar, Leonard Lausen, Balasubramaniam Srinivasan, Sheng Zha, Ruihong Huang, George Karypis (2023). HYTREL: Hypergraph-enhanced Tabular Data Representation Learning. NeurIPS, 2023 (spotlight).

Cite arXiv code

Pei (Patrick) Chen, Wenlin Yao, Hongming Zhang, Xiaoman Pan, Dian Yu, Dong Yu, Jianshu Chen (2023). ZeroKBC: A Comprehensive Benchmark for Zero-Shot Knowledge Base Completion. ICDMW 2022.

PDF Cite Dataset

Pei (Patrick) Chen, Haotian Xu, Cheng Zhang, Ruihong Huang (2022). Crossroads, Buildings and Neighborhoods: A Dataset for Fine-grained Location Recognition. NAACL 2022, long paper, acceptance rate: 21.96%.

PDF Cite Code Dataset

Pei (Patrick) Chen, Haibo Ding, Jun Araki, Ruihong Huang (2021). Explicitly Capturing Relations between Entity Mentions via Graph Neural Networks for Domain-specific Named Entity Recognition. ACL 2021, short paper, acceptance rate: 21.2%.

PDF Cite Code Dataset

Pei (Patrick) Chen, Kang Liu, Yubo Chen, Taifeng Wang, Jun Zhao (2021). Probing into the Root: A Dataset for Reason Extraction of Structural Events from Financial Documents. EACL 2021, short paper, acceptance rate: 24.7%.

PDF Cite Code Dataset

Pei (Patrick) Chen, Hang Yang, Kang Liu, Ruihong Huang, Yubo Chen, Taifeng Wang, Jun Zhao (2020). Reconstructing Event Regions for Event Extraction via Graph Attention Networks. AACL 2020, long paper, acceptance rate: 28.3%.

PDF Cite Dataset