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Found 6 papers, 1 papers with code
Large Language Models as Conversational Movie Recommenders: A User Study
This paper explores the effectiveness of using large language models (LLMs) for personalized movie recommendations from users' perspectives in an online field experiment.
What Are We Optimizing For? A Human-centric Evaluation of Deep Learning-based Movie Recommenders
In the past decade, deep learning (DL) models have gained prominence for their exceptional accuracy on benchmark datasets in recommender systems (RecSys).
Organizational Bulk Email Systems: Their Role and Performance in Remote Work
The COVID-19 pandemic has forced many employees to work from home.
Less Can Be More: Exploring Population Rating Dispositions with Partitioned Models in Recommender Systems
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.
Getting the Most from Eye-Tracking: User-Interaction Based Reading Region Estimation Dataset and Models
A single digital newsletter usually contains many messages (regions).
Recommender Systems Notation: Proposed Common Notation for Teaching and Research
In the course of years of teaching and research on recommender systems, we have seen the val-ue in adopting a consistent notation across our work.
