81 citations · 168 across the 7 of their papers we have counts for
7 papers
Transforming Podcast Preview Generation: From Expert Models to LLM-Based Systems
Winstead Zhu, Ann Clifton, Azin Ghazimatin +2
Discovering and evaluating long-form talk content such as videos and podcasts poses a significant challenge for users, as it requires a considerable time investment. Previews offer…
PODTILE: Facilitating Podcast Episode Browsing with Auto-generated Chapters
Azin Ghazimatin, Ekaterina Garmash, Gustavo Penha +14
Listeners of long-form talk-audio content, such as podcast episodes, often find it challenging to understand the overall structure and locate relevant sections. A practical solutio…
Counterfactual Explanations for Neural Recommenders
Khanh Hiep Tran, Azin Ghazimatin, Rishiraj Saha Roy
Understanding why specific items are recommended to users can significantly increase their trust and satisfaction in the system. While neural recommenders have become the state-of-…
ELIXIR: Learning from User Feedback on Explanations to Improve Recommender Models
Azin Ghazimatin, Soumajit Pramanik, Rishiraj Saha Roy +1
System-provided explanations for recommendations are an important component towards transparent and trustworthy AI. In state-of-the-art research, this is a one-way signal, though,…
PRINCE: Provider-side Interpretability with Counterfactual Explanations in Recommender Systems
Azin Ghazimatin, Oana Balalau, Rishiraj Saha Roy +1
Interpretable explanations for recommender systems and other machine learning models are crucial to gain user trust. Prior works that have focused on paths connecting users and ite…
FAIRY: A Framework for Understanding Relationships between Users' Actions and their Social Feeds
Azin Ghazimatin, Rishiraj Saha Roy, Gerhard Weikum
Users increasingly rely on social media feeds for consuming daily information. The items in a feed, such as news, questions, songs, etc., usually result from the complex interplay…
Team Selection For Prediction Tasks
MohammadAmin Fazli, Azin Ghazimatin, Jafar Habibi +1
Given a random variable and a set of experts , we describe a method for finding a subset of experts whose aggregated opinion best predicts the…