127 citations · 194 across the 6 of their papers we have counts for
6 papers
Investigating Reproducibility in Deep Learning-Based Software Fault Prediction
Adil Mukhtar, Dietmar Jannach, Franz Wotawa
Over the past few years, deep learning methods have been applied for a wide range of Software Engineering (SE) tasks, including in particular for the important task of automaticall…
Leveraging Large Language Models for Sequential Recommendation
Jesse Harte, Wouter Zorgdrager, Panos Louridas +3
Sequential recommendation problems have received increasing attention in research during the past few years, leading to the inception of a large variety of algorithmic approaches.…
On the Opportunities and Challenges of Offline Reinforcement Learning for Recommender Systems
Xiaocong Chen, Siyu Wang, Julian McAuley +2
Reinforcement learning serves as a potent tool for modeling dynamic user interests within recommender systems, garnering increasing research attention of late. However, a significa…
Semi-supervised Adversarial Learning for Complementary Item Recommendation
Koby Bibas, Oren Sar Shalom, Dietmar Jannach
Complementary item recommendations are a ubiquitous feature of modern e-commerce sites. Such recommendations are highly effective when they are based on collaborative signals like…
Recommender Systems: A Primer
Pablo Castells, Dietmar Jannach
Personalized recommendations have become a common feature of modern online services, including most major e-commerce sites, media platforms and social networks. Today, due to their…
Evaluating Conversational Recommender Systems: A Landscape of Research
Dietmar Jannach
Conversational recommender systems aim to interactively support online users in their information search and decision-making processes in an intuitive way. With the latest advances…