2 citations · 2 across the 2 of their papers we have counts for
2 papers
cs.HC2023
A Co-design Study for Multi-Stakeholder Job Recommender System Explanations
Roan Schellingerhout, Francesco Barile, Nava Tintarev
Recent legislation proposals have significantly increased the demand for eXplainable Artificial Intelligence (XAI) in many businesses, especially in so-called `high-risk' domains,…
cs.IR2023★ 2 cited
VideolandGPT: A User Study on a Conversational Recommender System
Mateo Gutierrez Granada, Dina Zilbershtein, Daan Odijk +1
This paper investigates how large language models (LLMs) can enhance recommender systems, with a specific focus on Conversational Recommender Systems that leverage user preferences…