| 2026 | CHI | AI Agents and the Future of Deliberation: Designing Human-AI Collaboration for Democratic Dialogue. | Weiyu Zhang, Simon Tangi Perrault, ShunYi Yeo, Jiaxin Pei, Anna De Liddo, Francesco Veri, Maurice Flechtner, Horacio Saggion |
| 2025 | ACL | Beyond Demographics: Fine-tuning Large Language Models to Predict Individuals' Subjective Text Perceptions. | Matthias Orlikowski, Jiaxin Pei, Paul Rttger, Philipp Cimiano, David Jurgens, Dirk Hovy |
| 2025 | CHI | User-Driven Value Alignment: Understanding Users' Perceptions and Strategies for Addressing Biased and Discriminatory Statements in AI Companions. | Xianzhe Fan, Qing Xiao, Xuhui Zhou, Jiaxin Pei, Maarten Sap, Zhicong Lu, Hong Shen |
| 2025 | CHI | Who Reaps All the Superchats? A Large-Scale Analysis of Income Inequality in Virtual YouTuber Livestreaming. | Ruijing Zhao, Brian Diep, Jiaxin Pei, Dongwook Yoon, David Jurgens, Jian Zhu |
| 2025 | NAACL | Sociodemographic Prompting is Not Yet an Effective Approach for Simulating Subjective Judgments with LLMs. | Huaman Sun, Jiaxin Pei, Minje Choi, David Jurgens |
| 2025 | NAACL | Causally Modeling the Linguistic and Social Factors that Predict Email Response. | Yinuo Xu, Hong Chen, Sushrita Rakshit, Aparna Ananthasubramaniam, Omkar Yadav, Mingqian Zheng, Michael Jiang, Lechen Zhang, Bowen Yi, Kenan Alkiek, Abraham Israeli, Bangzhao Shu, Hua Shen, Jiaxin Pei, Haotian Zhang, Miriam Schirmer, David Jurgens |
| 2024 | EMNLP | When "A Helpful Assistant" Is Not Really Helpful: Personas in System Prompts Do Not Improve Performances of Large Language Models. | Mingqian Zheng, Jiaxin Pei, Lajanugen Logeswaran, Moontae Lee, David Jurgens |
| 2024 | NAACL | Modeling and Detecting Company Risks from News. | Jiaxin Pei, Soumya Vadlamannati, Liang-Kang Huang, Daniel Preotiuc-Pietro, Xinyu Hua |
| 2023 | EMNLP | SuperTweetEval: A Challenging, Unified and Heterogeneous Benchmark for Social Media NLP Research. | Dimosthenis Antypas, Asahi Ushio, Francesco Barbieri, Leonardo Neves, Kiamehr Rezaee, Luis Espinosa Anke, Jiaxin Pei, Jos Camacho-Collados |
| 2023 | EMNLP | Do LLMs Understand Social Knowledge? Evaluating the Sociability of Large Language Models with SocKET Benchmark. | Minje Choi, Jiaxin Pei, Sagar Kumar, Chang Shu, David Jurgens |
| 2022 | EMNLP | Modeling Information Change in Science Communication with Semantically Matched Paraphrases. | Dustin Wright, Jiaxin Pei, David Jurgens, Isabelle Augenstein |
| 2022 | EMNLP | POTATO: The Portable Text Annotation Tool. | Jiaxin Pei, Aparna Ananthasubramaniam, Xingyao Wang, Naitian Zhou, Apostolos Dedeloudis, Jackson Sargent, David Jurgens |
| 2021 | EMNLP | Measuring Sentence-Level and Aspect-Level (Un)certainty in Science Communications. | Jiaxin Pei, David Jurgens |
| 2020 | ACL | Pre-train and Plug-in: Flexible Conditional Text Generation with Variational Auto-Encoders. | Yu Duan, Canwen Xu, Jiaxin Pei, Jialong Han, Chenliang Li |
| 2020 | ACL | MATINF: A Jointly Labeled Large-Scale Dataset for Classification, Question Answering and Summarization. | Canwen Xu, Jiaxin Pei, Hongtao Wu, Yiyu Liu, Chenliang Li |
| 2020 | EMNLP | Quantifying Intimacy in Language. | Jiaxin Pei, David Jurgens |
| 2019 | WWW | DLocRL: A Deep Learning Pipeline for Fine-Grained Location Recognition and Linking in Tweets. | Canwen Xu, Jing Li, Xiangyang Luo, Jiaxin Pei, Chenliang Li, Donghong Ji |
| 2018 | EMNLP | S2SPMN: A Simple and Effective Framework for Response Generation with Relevant Information. | Jiaxin Pei, Chenliang Li |