Sotabase

Career

· Postdoctoral Researcher, Stanford University
· Ph.D. in Information Science, University of Michigan
· Undergraduate Student, Wuhan University

Publications (51)

Do LLMs Understand Social Knowledge? Evaluating the Sociability of Large Language Models with SocKET Benchmark
Conference on Empirical Methods in Natural Language Processing · 2023
94
cited
POTATO: The Portable Text Annotation Tool
Conference on Empirical Methods in Natural Language Processing · 2022
91
cited
Quantifying Intimacy in Language
Conference on Empirical Methods in Natural Language Processing · 2020
58
cited
When Do Annotator Demographics Matter? Measuring the Influence of Annotator Demographics with the POPQUORN Dataset
Law · 2023
54
cited
Pre-train and Plug-in: Flexible Conditional Text Generation with Variational Auto-Encoders
Annual Meeting of the Association for Computational Linguistics · 2019
45
cited
Measuring Sentence-Level and Aspect-Level (Un)certainty in Science Communications
Conference on Empirical Methods in Natural Language Processing · 2021
38
cited
When"A Helpful Assistant"Is Not Really Helpful: Personas in System Prompts Do Not Improve Performances of Large Language Models
2023
36
cited
DLocRL: A Deep Learning Pipeline for Fine-Grained Location Recognition and Linking in Tweets
The Web Conference · 2019
30
cited
SemEval-2023 Task 9: Multilingual Tweet Intimacy Analysis
International Workshop on Semantic Evaluation · 2022
29
cited
Political-LLM: Large Language Models in Political Science
arXiv.org · 2024
27
cited
Sociodemographic Prompting is Not Yet an Effective Approach for Simulating Subjective Judgments with LLMs
North American Chapter of the Association for Computational Linguistics · 2023
26
cited
Beyond Demographics: Fine-tuning Large Language Models to Predict Individuals' Subjective Text Perceptions
Annual Meeting of the Association for Computational Linguistics · 2025
24
cited
Future of Work with AI Agents: Auditing Automation and Augmentation Potential across the U.S. Workforce
arXiv.org · 2025
17
cited
Modeling Information Change in Science Communication with Semantically Matched Paraphrases
Conference on Empirical Methods in Natural Language Processing · 2022
16
cited
SuperTweetEval: A Challenging, Unified and Heterogeneous Benchmark for Social Media NLP Research
Conference on Empirical Methods in Natural Language Processing · 2023
15
cited
When "A Helpful Assistant" Is Not Really Helpful: Personas in System Prompts Do Not Improve Performances of Large Language Models
Conference on Empirical Methods in Natural Language Processing · 2024
15
cited
MATINF: A Jointly Labeled Large-Scale Dataset for Classification, Question Answering and Summarization
Annual Meeting of the Association for Computational Linguistics · 2020
14
cited
S2SPMN: A Simple and Effective Framework for Response Generation with Relevant Information
Conference on Empirical Methods in Natural Language Processing · 2018
12
cited
Targeted Sentiment Analysis: A Data-Driven Categorization
arXiv.org · 2019
9
cited
A Moral- and Event- Centric Inspection of Gender Bias in Fairy Tales at A Large Scale
arXiv.org · 2022
7
cited
Sotabase