3 papers
cs.IR2026
Hybrid Cold-Start Recommender System for Closure Model Selection in Multiphase Flow Simulations
S. Hänsch, A. Sajdoková, A. Rębowski +6
Selecting appropriate physical models is a critical yet difficult step in many areas of computational science and engineering. In multiphase Computational Fluid Dynamics (CFD), pra…
cs.IR2025
The Future is Sparse: Embedding Compression for Scalable Retrieval in Recommender Systems
Petr Kasalický, Martin Spišák, Vojtěch Vančura +3
Industry-scale recommender systems face a core challenge: representing entities with high cardinality, such as users or items, using dense embeddings that must be accessible during…
cs.LG2025
Reasoning-Grounded Natural Language Explanations for Language Models
Vojtech Cahlik, Rodrigo Alves, Pavel Kordik
We propose a large language model explainability technique for obtaining faithful natural language explanations by grounding the explanations in a reasoning process. When converted…