14 citations · 29 across the 8 of their papers we have counts for
8 papers
Balancing Domestic and Global Perspectives: Evaluating Dual-Calibration and LLM-Generated Nudges for Diverse News Recommendation
Ruixuan Sun, Matthew Zent, Minzhu Zhao +3
In this study, we applied the ``personalized diversity nudge framework'' with the goal of expanding user reading coverage in terms of news locality (i.e., domestic and world news).…
Co-Authoring the Self: A Human-AI Interface for Interest Reflection in Recommenders
Ruixuan Sun, Junyuan Wang, Sanjali Roy +1
Natural language-based user profiles in recommender systems have been explored for their interpretability and potential to help users scrutinize and refine their interests, thereby…
Large Language Models as Conversational Movie Recommenders: A User Study
Ruixuan Sun, Xinyi Li, Avinash Akella +1
This paper explores the effectiveness of using large language models (LLMs) for personalized movie recommendations from users' perspectives in an online field experiment. Our study…
What Are We Optimizing For? A Human-centric Evaluation of Deep Learning-based Movie Recommenders
Ruixuan Sun, Xinyi Wu, Avinash Akella +3
In the past decade, deep learning (DL) models have gained prominence for their exceptional accuracy on benchmark datasets in recommender systems (RecSys). However, their evaluation…
Interactive Content Diversity and User Exploration in Online Movie Recommenders: A Field Experiment
Ruixuan Sun, Avinash Akella, Ruoyan Kong +2
Recommender systems often struggle to strike a balance between matching users' tastes and providing unexpected recommendations. When recommendations are too narrow and fail to cove…
Less Can Be More: Exploring Population Rating Dispositions with Partitioned Models in Recommender Systems
Ruixuan Sun, Ruoyan Kong, Qiao Jin +1
In this study, we partition users by rating disposition - looking first at their percentage of negative ratings, and then at the general use of the rating scale. We hypothesize tha…
Getting the Most from Eye-Tracking: User-Interaction Based Reading Region Estimation Dataset and Models
Ruoyan Kong, Ruixuan Sun, Charles Chuankai Zhang +4
A single digital newsletter usually contains many messages (regions). Users' reading time spent on, and read level (skip/skim/read-in-detail) of each message is important for platf…
Multi-Objective Personalization in Multi-Stakeholder Organizational Bulk E-mail: A Field Experiment
Ruoyan Kong, Chuankai Zhang, Ruixuan Sun +3
Bulk email is often used in organizations to communicate ``important-to-organization'' messages such as policy changes, organizational plans, and administrative updates. However, n…