130 citations · 273 across the 19 of their papers we have counts for
7 papers · 1 filter
Linking Faces and Voices Across Languages: Insights from the FAME 2026 Challenge
Marta Moscati, Ahmed Abdullah, Muhammad Saad Saeed +7
Over half of the world's population is bilingual and people often communicate under multilingual scenarios. The Face-Voice Association in Multilingual Environments (FAME) 2026 Chal…
Face-voice Association in Multilingual Environments (FAME) 2026 Challenge Evaluation Plan
Marta Moscati, Ahmed Abdullah, Muhammad Saad Saeed +7
The advancements of technology have led to the use of multimodal systems in various real-world applications. Among them, audio-visual systems are among the most widely used multimo…
Single-Branch Network Architectures to Close the Modality Gap in Multimodal Recommendation
Christian Ganhör, Marta Moscati, Anna Hausberger +2
Traditional recommender systems rely on collaborative filtering, using past user-item interactions to help users discover new items in a vast collection. In cold start, i.e., when…
Music4All A+A: A Multimodal Dataset for Music Information Retrieval Tasks
Jonas Geiger, Marta Moscati, Shah Nawaz +1
Music is characterized by aspects related to different modalities, such as the audio signal, the lyrics, or the music video clips. This has motivated the development of multimodal…
Parameter-Efficient Single Collaborative Branch for Recommendation
Marta Moscati, Shah Nawaz, Markus Schedl
Recommender Systems (RS) often rely on representations of users and items in a joint embedding space and on a similarity metric to compute relevance scores. In modern RS, the modul…
Familiarizing with Music: Discovery Patterns for Different Music Discovery Needs
Marta Moscati, Darius Afchar, Markus Schedl +1
Humans have the tendency to discover and explore. This natural tendency is reflected in data from streaming platforms as the amount of previously unknown content accessed by users.…
Unsupervised Graph Embeddings for Session-based Recommendation with Item Features
Andreas Peintner, Marta Moscati, Emilia Parada-Cabaleiro +2
In session-based recommender systems, predictions are based on the user's preceding behavior in the session. State-of-the-art sequential recommendation algorithms either use graph…