1 citations · 1 across the 1 of their papers we have counts for
4 papers
Efficient Learning of Sparse Representations from Interactions
VojtÄch VanÄura, Martin Spišák, Rodrigo Alves +1
Behavioral patterns captured in embeddings learned from interaction data are pivotal across various stages of production recommender systems. However, in the initial retrieval stag…
From Knots to Knobs: Towards Steerable Collaborative Filtering Using Sparse Autoencoders
Martin Spišák, Ladislav Peška, Petr Škoda +2
Sparse autoencoders (SAEs) have recently emerged as pivotal tools for introspection into large language models. SAEs can uncover high-quality, interpretable features at different l…
Evaluating Keyframe Layouts for Visual Known-Item Search in Homogeneous Collections
Bastian Jäckl, JiÅà Kruchina, Lucas Joos +3
Multimodal deep-learning models power interactive video retrieval by ranking keyframes in response to textual queries. Despite these advances, users must still browse ranked candid…
Personalisation of d'Hondt's algorithm and its use in recommender ecosystems
Stepan Balcar, Ladislav Peska, Peter Vojtas
In the area of recommender systems, we are dealing with aggregations and potential of personalisation in ecosystems. Personalisation is based on separate aggregation models for eac…