52 citations · 81 across the 9 of their papers we have counts for
10 papers
Beyond Better Ideas: How Human-AI Collaboration Shapes Scientific Ideas and Human Perceptions
Qian Chen, Saatvik Pradhan, Janice Ahn +7
As AI increasingly becomes a collaborator in scientific research, its impact may extend beyond improving ideas to reshaping how they are evaluated, attributed, and perceived by hum…
Legitimizing, Developing, and Sustaining Feminist HCI in East Asia: Challenges and Opportunities
Runhua Zhang, Ruyuan Wan, Jiaqi Li +7
Feminist HCI has been rapidly developing in East Asian contexts in recent years. The region's unique cultural and political backgrounds have contributed valuable, situated knowledg…
Hashtag Re-Appropriation for Audience Control on Recommendation-Driven Social Media Xiaohongshu (rednote)
Ruyuan Wan, Lingbo Tong, Tiffany Knearem +3
Algorithms have played a central role in personalized recommendations on social media. However, they also present significant obstacles for content creators trying to predict and m…
CoCoLoFa: A Dataset of News Comments with Common Logical Fallacies Written by LLM-Assisted Crowds
Min-Hsuan Yeh, Ruyuan Wan, Ting-Hao 'Kenneth' Huang
Detecting logical fallacies in texts can help users spot argument flaws, but automating this detection is not easy. Manually annotating fallacies in large-scale, real-world text da…
CoCo Matrix: Taxonomy of Cognitive Contributions in Co-writing with Intelligent Agents
Ruyuan Wan, Simret Gebreegziabhe, Toby Jia-Jun Li +1
In recent years, there has been a growing interest in employing intelligent agents in writing. Previous work emphasizes the evaluation of the quality of end product-whether it was…
Annotation Imputation to Individualize Predictions: Initial Studies on Distribution Dynamics and Model Predictions
London Lowmanstone, Ruyuan Wan, Risako Owan +2
Annotating data via crowdsourcing is time-consuming and expensive. Due to these costs, dataset creators often have each annotator label only a small subset of the data. This leads…
Everyone's Voice Matters: Quantifying Annotation Disagreement Using Demographic Information
Ruyuan Wan, Jaehyung Kim, Dongyeop Kang
In NLP annotation, it is common to have multiple annotators label the text and then obtain the ground truth labels based on the agreement of major annotators. However, annotators a…
User or Labor: An Interaction Framework for Human-Machine Relationships in NLP
Ruyuan Wan, Naome Etori, Karla Badillo-Urquiola +1
The bridging research between Human-Computer Interaction and Natural Language Processing is developing quickly these years. However, there is still a lack of formative guidelines t…
A Conversational Agent System for Dietary Supplements Use
Esha Singh, Anu Bompelli, Ruyuan Wan +3
Dietary supplements (DS) have been widely used by consumers, but the information around the efficacy and safety of DS is disparate or incomplete, thus creating barriers for consume…
Social and behavioral determinants of health in the era of artificial intelligence with electronic health records: A scoping review
Anusha Bompelli, Yanshan Wang, Ruyuan Wan +8
Background: There is growing evidence that social and behavioral determinants of health (SBDH) play a substantial effect in a wide range of health outcomes. Electronic health recor…