473 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Microsoft (United States)US3 papers
- National Institute of Standards and TechnologyUS3 papers
- University College LondonGB3 papers
- University of Maryland, College ParkUS3 papers
- Boise State UniversityUS2 papers
- Carnegie Mellon UniversityUS2 papers
- Center for Nanoscale Science and TechnologyUS2 papers
- Cornell UniversityUS2 papers
- Drexel UniversityUS2 papers
- Korea Institute of Science and TechnologyKR2 papers
- Massachusetts Institute of TechnologyUS2 papers
- Physical Measurement LaboratoryUS2 papers
15 papers · 1 filter
Cold-Starting Podcast Ads and Promotions with Multi-Task Learning on Spotify
Shivam Verma, Hannes Karlbom, Yu Zhao +4
We present a unified multi-objective model for targeting both advertisements and promotions within the Spotify podcast ecosystem. Our approach addresses key challenges in personali…
Evaluating Podcast Recommendations with Profile-Aware LLM-as-a-Judge
Francesco Fabbri, Gustavo Penha, Edoardo D'Amico +7
Evaluating personalized recommendations remains a central challenge, especially in long-form audio domains like podcasts, where traditional offline metrics suffer from exposure bia…
Semantic IDs for Music Recommendation
M. Jeffrey Mei, Florian Henkel, Samuel E. Sandberg +2
Training recommender systems for next-item recommendation often requires unique embeddings to be learned for each item, which may take up most of the trainable parameters for a mod…
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…
Prompt-to-Slate: Diffusion Models for Prompt-Conditioned Slate Generation
Federico Tomasi, Francesco Fabbri, Justin Carter +3
Slate generation is a common task in streaming and e-commerce platforms, where multiple items are presented together as a list or ``slate''. Traditional systems focus mostly on ite…
MS MARCO Web Search: a Large-scale Information-rich Web Dataset with Millions of Real Click Labels
Qi Chen, Xiubo Geng, Corby Rosset +28
Recent breakthroughs in large models have highlighted the critical significance of data scale, labels and modals. In this paper, we introduce MS MARCO Web Search, the first large-s…
Distributionally-Informed Recommender System Evaluation
Michael D. Ekstrand, Ben Carterette, Fernando Diaz
Current practice for evaluating recommender systems typically focuses on point estimates of user-oriented effectiveness metrics or business metrics, sometimes combined with additio…
Building Human Values into Recommender Systems: An Interdisciplinary Synthesis
Jonathan Stray, Alon Halevy, Parisa Assar +18
Recommender systems are the algorithms which select, filter, and personalize content across many of the worlds largest platforms and apps. As such, their positive and negative effe…
Mostra: A Flexible Balancing Framework to Trade-off User, Artist and Platform Objectives for Music Sequencing
Emanuele Bugliarello, Rishabh Mehrotra, James Kirk +1
We consider the task of sequencing tracks on music streaming platforms where the goal is to maximise not only user satisfaction, but also artist- and platform-centric objectives, n…
Podcast Metadata and Content: Episode Relevance andAttractiveness in Ad Hoc Search
Ben Carterette, Rosie Jones, Gareth F. Jones +6
Rapidly growing online podcast archives contain diverse content on a wide range of topics. These archives form an important resource for entertainment and professional use, but the…
Estimation of Fair Ranking Metrics with Incomplete Judgments
Ömer Kırnap, Fernando Diaz, Asia Biega +3
There is increasing attention to evaluating the fairness of search system ranking decisions. These metrics often consider the membership of items to particular groups, often identi…
Current Challenges and Future Directions in Podcast Information Access
Rosie Jones, Hamed Zamani, Markus Schedl +11
Podcasts are spoken documents across a wide-range of genres and styles, with growing listenership across the world, and a rapidly lowering barrier to entry for both listeners and c…
Recommending Podcasts for Cold-Start Users Based on Music Listening and Taste
Zahra Nazari, Christophe Charbuillet, Johan Pages +4
Recommender systems are increasingly used to predict and serve content that aligns with user taste, yet the task of matching new users with relevant content remains a challenge. We…
Large-Scale User Modeling with Recurrent Neural Networks for Music Discovery on Multiple Time Scales
Cedric De Boom, Rohan Agrawal, Samantha Hansen +5
The amount of content on online music streaming platforms is immense, and most users only access a tiny fraction of this content. Recommender systems are the application of choice…
Auditing Search Engines for Differential Satisfaction Across Demographics
Rishabh Mehrotra, Ashton Anderson, Fernando Diaz +3
Many online services, such as search engines, social media platforms, and digital marketplaces, are advertised as being available to any user, regardless of their age, gender, or o…