145 citations · 186 across the 8 of their papers we have counts for
6 papers · 1 filter
Evaluating Brand Retrieval and Ranking in Large Language Model Recommendations
Edward Malthouse, Kun-Yu Lee, Jing Yang +2
Large language models (LLMs) are increasingly used for product recommendation, but evaluating their recommendations presents challenges that differ from conventional information re…
Exploring Fine-tuning ChatGPT for News Recommendation
Xinyi Li, Yongfeng Zhang, Edward C Malthouse
News recommendation systems (RS) play a pivotal role in the current digital age, shaping how individuals access and engage with information. The fusion of natural language processi…
A Preliminary Study of ChatGPT on News Recommendation: Personalization, Provider Fairness, Fake News
Xinyi Li, Yongfeng Zhang, Edward C. Malthouse
Online news platforms commonly employ personalized news recommendation methods to assist users in discovering interesting articles, and many previous works have utilized language m…
PBNR: Prompt-based News Recommender System
Xinyi Li, Yongfeng Zhang, Edward C. Malthouse
Online news platforms often use personalized news recommendation methods to help users discover articles that align with their interests. These methods typically predict a matching…
Toward the Next Generation of News Recommender Systems
Himan Abdollahpouri, Edward Malthouse, Joseph Konstan +2
This paper proposes a vision and research agenda for the next generation of news recommender systems (RS), called the table d'hote approach. A table d'hote (translates as host's ta…
User-centered Evaluation of Popularity Bias in Recommender Systems
Himan Abdollahpouri, Masoud Mansoury, Robin Burke +2
Recommendation and ranking systems are known to suffer from popularity bias; the tendency of the algorithm to favor a few popular items while under-representing the majority of oth…