5 citations · 9 across the 22 of their papers we have counts for
4 papers · 1 filter
Simultaneous Unlearning of Multiple Protected User Attributes From Variational Autoencoder Recommenders Using Adversarial Training
Gustavo Escobedo, Christian Ganhör, Stefan Brandl +2
In widely used neural network-based collaborative filtering models, users' history logs are encoded into latent embeddings that represent the users' preferences. In this setting, t…
A Multimodal Single-Branch Embedding Network for Recommendation in Cold-Start and Missing Modality Scenarios
Christian Ganhör, Marta Moscati, Anna Hausberger +2
Most recommender systems adopt collaborative filtering (CF) and provide recommendations based on past collective interactions. Therefore, the performance of CF algorithms degrades…
Chameleon: Images Are What You Need For Multimodal Learning Robust To Missing Modalities
Muhammad Irzam Liaqat, Shah Nawaz, Muhammad Zaigham Zaheer +5
Multimodal learning has demonstrated remarkable performance improvements over unimodal architectures. However, multimodal learning methods often exhibit deteriorated performances i…
Segment Any Text: A Universal Approach for Robust, Efficient and Adaptable Sentence Segmentation
Markus Frohmann, Igor Sterner, Ivan Vulić +2
Segmenting text into sentences plays an early and crucial role in many NLP systems. This is commonly achieved by using rule-based or statistical methods relying on lexical features…