Scholar
Paiheng Xu
Google Scholar ID: fy17k4kAAAAJ
University of Maryland, College Park
Citations & Impact
Citations
419
H-index
10
i10-index
10
Publications
17
Co-authors
14
list available
Publications
Resume (English only)
Academic Achievements
- - Survey on Large Language Models and Causal Inference accepted to Findings of NAACL 2025
- - Paper on concept level spurious correlations for text classification accepted to ACL 2024
- - The Promises and Pitfalls of Using Language Models to Measure Instruction Quality in Education accepted to NAACL 2024
- - Twitter social mobility data reveal demographic variations in social distancing practices during the COVID-19 pandemic published in Scientific Reports
Research Experience
- - Intern at Adobe Research, working on personalization and style understanding for designers
- - Ph.D. student at UMD's CLIP lab, closely working with Jing Liu, Louiqa Raschid, Vanessa Frias-Martinez, and Furong Huang
- - Worked at the Center for Language and Speech Processing, Johns Hopkins University
Education
- - Ph.D. in Computer Science, University of Maryland, Advisor: Wei Ai
- - M.S.E. in Computer Science, Johns Hopkins University, Advisor: Mark Dredze
- - B.E. in Computer Science, Southwest University, Advisors: Yong Deng (Complex Network), Tao Zhou (Human Mobility)
Background
- Research Interests: Natural Language Processing (NLP) and Computational Social Science. Interested in uncovering patterns from data and investigating how these patterns correlate with human behaviors, particularly in education and social media contexts. Also studies how such patterns influence the behaviors of language models.
