53 citations · 191 across the 13 of their papers we have counts for
14 papers
Large Language Models are Competitive Near Cold-start Recommenders for Language- and Item-based Preferences
Scott Sanner, Krisztian Balog, Filip Radlinski +2
Traditional recommender systems leverage users' item preference history to recommend novel content that users may like. However, modern dialog interfaces that allow users to expres…
Measuring the Impact of Explanation Bias: A Study of Natural Language Justifications for Recommender Systems
Krisztian Balog, Filip Radlinski, Andrey Petrov
Despite the potential impact of explanations on decision making, there is a lack of research on quantifying their effect on users' choices. This paper presents an experimental prot…
Beyond Single Items: Exploring User Preferences in Item Sets with the Conversational Playlist Curation Dataset
Arun Tejasvi Chaganty, Megan Leszczynski, Shu Zhang +3
Users in consumption domains, like music, are often able to more efficiently provide preferences over a set of items (e.g. a playlist or radio) than over single items (e.g. songs).…
Resolving Indirect Referring Expressions for Entity Selection
Mohammad Javad Hosseini, Filip Radlinski, Silvia Pareti +1
Recent advances in language modeling have enabled new conversational systems. In particular, it is often desirable for people to make choices among specified options when using suc…
On Natural Language User Profiles for Transparent and Scrutable Recommendation
Filip Radlinski, Krisztian Balog, Fernando Diaz +2
Natural interaction with recommendation and personalized search systems has received tremendous attention in recent years. We focus on the challenge of supporting people's understa…
Generating Usage-related Questions for Preference Elicitation in Conversational Recommender Systems
Ivica Kostric, Krisztian Balog, Filip Radlinski
A key distinguishing feature of conversational recommender systems over traditional recommender systems is their ability to elicit user preferences using natural language. Currentl…