Jiaxin Pei

According to our database, Jiaxin Pei authored at least 33 papers between 2018 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

Modeling Public Perceptions of Science in Media.

Jiaxin Pei, Dustin Wright, Isabelle Augenstein, David Jurgens

CoRR, June, 2025

Future of Work with AI Agents: Auditing Automation and Augmentation Potential across the U.S. Workforce.

Yijia Shao, Humishka Zope, Yucheng Jiang, Jiaxin Pei, David Nguyen, Erik Brynjolfsson, Diyi Yang

CoRR, June, 2025

The Automated but Risky Game: Modeling Agent-to-Agent Negotiations and Transactions in Consumer Markets.

Shenzhe Zhu, Jiao Sun, Yi Nian, Tobin South, Alex Pentland, Jiaxin Pei

CoRR, June, 2025

Writing Patterns Reveal a Hidden Division of Labor in Scientific Teams.

Lulin Yang, Jiaxin Pei, Lingfei Wu

CoRR, April, 2025

Hidden Division of Labor in Scientific Teams Revealed Through 1.6 Million LaTeX Files.

Jiaxin Pei, Lulin Yang, Lingfei Wu

CoRR, February, 2025

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

Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies, 2025

Sociodemographic Prompting is Not Yet an Effective Approach for Simulating Subjective Judgments with LLMs.

Huaman Sun, Jiaxin Pei, Minje Choi, David Jurgens

Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies, 2025

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

Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems, 2025

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

Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems, 2025

Beyond Demographics: Fine-tuning Large Language Models to Predict Individuals' Subjective Text Perceptions.

Matthias Orlikowski, Jiaxin Pei, Paul Röttger, Philipp Cimiano, David Jurgens, Dirk Hovy

Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2025

2024

Political-LLM: Large Language Models in Political Science.

Lincan Li, Jiaqi Li, Catherine Chen, Fred Gui, Hongjia Yang, Chenxiao Yu, Zhengguang Wang, Jianing Cai, Junlong Aaron Zhou, Bolin Shen, Alex Qian, Weixin Chen, Zhongkai Xue, Lichao Sun, Lifang He, Hanjie Chen, Kaize Ding, Zijian Du, Fangzhou Mu, Jiaxin Pei, Jieyu Zhao, Swabha Swayamdipta, Willie Neiswanger, Hua Wei, Xiyang Hu, Shixiang Zhu, Tianlong Chen, Yingzhou Lu, Yang Shi, Lianhui Qin, Tianfan Fu, Zhengzhong Tu, Yuzhe Yang, Jaemin Yoo, Jiaheng Zhang, Ryan A. Rossi, Liang Zhan, Liang Zhao, Emilio Ferrara, Yan Liu, Furong Huang, Xiangliang Zhang, Lawrence Rothenberg, Shuiwang Ji, Philip S. Yu, Yue Zhao, Yushun Dong

CoRR, 2024

Modeling and Detecting Company Risks from News.

Jiaxin Pei, Soumya Vadlamannati, Liang-Kang Huang, Daniel Preotiuc-Pietro, Xinyu Hua

Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies: Industry Track, 2024

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

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2024, 2024

2023

Is "A Helpful Assistant" the Best Role for Large Language Models? A Systematic Evaluation of Social Roles in System Prompts.

Mingqian Zheng, Jiaxin Pei, David Jurgens

CoRR, 2023

Aligning with Whom? Large Language Models Have Gender and Racial Biases in Subjective NLP Tasks.

Huaman Sun, Jiaxin Pei, Minje Choi, David Jurgens

CoRR, 2023

Exploring Linguistic Style Matching in Online Communities: The Role of Social Context and Conversation Dynamics.

Aparna Ananthasubramaniam, Hong Chen, Jason Yan, Kenan Alkiek, Jiaxin Pei, Agrima Seth, Lavinia Dunagan, Minje Choi, Benjamin Litterer, David Jurgens

CoRR, 2023

When Do Annotator Demographics Matter? Measuring the Influence of Annotator Demographics with the POPQUORN Dataset.

Jiaxin Pei, David Jurgens

CoRR, 2023

SemEval-2023 Task 9: Multilingual Tweet Intimacy Analysis.

Jiaxin Pei, Vítor Silva, Maarten W. Bos, Yozen Liu, Leonardo Neves, David Jurgens, Francesco Barbieri

Proceedings of the The 17th International Workshop on Semantic Evaluation, 2023

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

Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

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, José Camacho-Collados

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023

2022

A Moral- and Event- Centric Inspection of Gender Bias in Fairy Tales at A Large Scale.

Kyrie Zhixuan Zhou, Jiao Sun, Jiaxin Pei, Nanyun Peng, Jinjun Xiong

CoRR, 2022

SemEval 2023 Task 9: Multilingual Tweet Intimacy Analysis.

Jiaxin Pei, Vítor Silva, Maarten W. Bos, Yozon Liu, Leonardo Neves, David Jurgens, Francesco Barbieri

CoRR, 2022

POTATO: The Portable Text Annotation Tool.

Jiaxin Pei, Aparna Ananthasubramaniam, Xingyao Wang, Naitian Zhou, Apostolos Dedeloudis, Jackson Sargent, David Jurgens

Proceedings of the The 2022 Conference on Empirical Methods in Natural Language Processing, 2022

Modeling Information Change in Science Communication with Semantically Matched Paraphrases.

Dustin Wright, Jiaxin Pei, David Jurgens, Isabelle Augenstein

Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, 2022

2021

Measuring Sentence-Level and Aspect-Level (Un)certainty in Science Communications.

Jiaxin Pei, David Jurgens

Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021

2020

Quantifying Intimacy in Language.

Jiaxin Pei, David Jurgens

Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, 2020

MATINF: A Jointly Labeled Large-Scale Dataset for Classification, Question Answering and Summarization.

Canwen Xu, Jiaxin Pei, Hongtao Wu, Yiyu Liu, Chenliang Li

Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, 2020

Pre-train and Plug-in: Flexible Conditional Text Generation with Variational Auto-Encoders.

Yu Duan, Canwen Xu, Jiaxin Pei, Jialong Han, Chenliang Li

Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, 2020

2019

Pre-train and Plug-in: Flexible Conditional Text Generation with Variational Auto-Encoders.

Yu Duan, Jiaxin Pei, Canwen Xu, Chenliang Li

CoRR, 2019

SUM: Suboptimal Unitary Multi-task Learning Framework for Spatiotemporal Data Prediction.

Qichen Li, Jiaxin Pei, Jianding Zhang, Bo Han

CoRR, 2019

Targeted Sentiment Analysis: A Data-Driven Categorization.

Jiaxin Pei, Aixin Sun, Chenliang Li

CoRR, 2019

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

Proceedings of the World Wide Web Conference, 2019

2018

S2SPMN: A Simple and Effective Framework for Response Generation with Relevant Information.

Jiaxin Pei, Chenliang Li

Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, Brussels, Belgium, October 31, 2018