13 citations · 27 across the 5 of their papers we have counts for
5 papers
Diffusion Recommender Models and the Illusion of Progress: A Concerning Study of Reproducibility and a Conceptual Mismatch
Michael Benigni, Maurizio Ferrari Dacrema, Dietmar Jannach
Countless new machine learning models are published every year and are reported to significantly advance the state-of-the-art in top-n recommendation. However, earlier reproducibil…
A Worrying Reproducibility Study of Intent-Aware Recommendation Models
Faisal Shehzad, Maurizio Ferrari Dacrema, Dietmar Jannach
Lately, we have observed a growing interest in intent-aware recommender systems (IARS). The promise of such systems is that they are capable of generating better recommendations by…
Improving Sequential Recommendations with LLMs
Artun Boz, Wouter Zorgdrager, Zoe Kotti +5
The sequential recommendation problem has attracted considerable research attention in the past few years, leading to the rise of numerous recommendation models. In this work, we e…
Team-related Features in Code Review Prediction Models
Eduardo Witter, Ingrid Nunes, Dietmar Jannach
Modern Code Review (MCR) is an informal tool-assisted quality assurance practice. It relies on the asynchronous communication among the authors of code changes and reviewers, who a…
Performance Comparison of Session-based Recommendation Algorithms based on GNNs
Faisal Shehzad, Dietmar Jannach
In session-based recommendation settings, a recommender system has no access to long-term user profiles and thus has to base its suggestions on the user interactions that are obser…