2025
Show or Tell? Modeling the evolution of request-making in Human-LLM conversations
Shengqi Zhu, Jeffrey M. Rzeszotarski, David Mimno
arXiv Preprint, August 2025
TBD
Navigating the Fog: How University Students Recalibrate Sensemaking Practices to Address Plausible Falsehoods in LLM Outputs
Chao Zhang, Shengqi Zhu, Xinyu Yang, Yu-Chia Tseng, Shenrong Jiang, Jeffrey M. Rzeszotarski
Proceedings of the 7th ACM Conference on Conversational User Interfaces (CUI), 2025
TBD
Data Paradigms in the Era of LLMs: On the Opportunities and Challenges of Qualitative Data in the WILD
Shengqi Zhu, Jeffrey M. Rzeszotarski, David Mimno
Proceedings of the Extended Abstracts of the CHI Conference on Human Factors in Computing Systems (CHI LBW), 2025
TBD
What We Talk About When We Talk About LMs: Implicit Paradigm Shifts and the Ship of Language Models
Shengqi Zhu, Jeffrey M. Rzeszotarski
Proceedings of the Nations of the Americas Chapter of the Association for Computational Linguistics (NAACL), 2025
TBD (image source: SRF Kultur Sternstunden)
Million Eyes on the “Robot Umps”: The Case for Studying Sports in HRI Through Baseball
Project led by Waki Kamino and Andrea Wen-Yi Wang; served as one of the 23 sub-section authors.
the 20th ACM/IEEE International Conference on Human-Robot Interaction (HRI), 2025
TBD
2024
“Get Their Hands Dirty, Not Mine”: On Researcher-Annotator Collaboration and the Agency of Annotators
Shengqi Zhu, Jeffrey M. Rzeszotarski
Findings of the Association for Computational Linguistics (ACL Findings), 2024
TBD
2023 and Earlier
Prior to Cornell, I have mainly published with my long-time mentor and collaborator, Quzhe Huang. Many of my explorations during this period have fundamentally inspired my thoughts on NLP and language data in the real world, e.g., the application of noisy annotations, and the compromised effectiveness & problematic setups of NLP tasks under practical constraints.
Please see my Google Scholar profile for the full list of my earlier work published at ACL 2021/2022/2023.