Deep Variational Autoencoder with Shallow Parallel Path for Top-N Recommendation (VASP). - Vojtech Vancura; Pavel Kordík (ICANN (5), 2021)

Neural Basket Embedding for Sequential Recommendation. - Vojtech Vancura (RecSys, 2021)

Offline evaluation of the serendipity in recommendation systems. - Daniil Pastukhov; Stanislav Kuznetsov; Vojtech Vancura; Pavel Kordík (CSIT, 2022)

RepSys: Framework for Interactive Evaluation of Recommender Systems. - Jan Safarík; Vojtech Vancura; Pavel Kordík (RecSys, 2022)

Scalable Linear Shallow Autoencoder for Collaborative Filtering. - Vojtech Vancura; Rodrigo Alves; Petr Kasalický; Pavel Kordík (RecSys, 2022)

Scalable and Explainable Linear Shallow Autoencoders for Collaborative Filtering from Industrial Perspective. - Vojtech Vancura (UMAP, 2023)

beeFormer: Bridging the Gap Between Semantic and Interaction Similarity in Recommender Systems. - Vojtech Vancura; Pavel Kordík; Milan Straka (RecSys, 2024)

Mitigating Risks in Marketplace Semantic Search: A Dataset for Harmful and Sensitive Query Alignment. - Filip Spacek; Vojtech Vancura; Pavel Kordík (UMAP, 2025)

The Future is Sparse: Embedding Compression for Scalable Retrieval in Recommender Systems. - Petr Kasalický; Martin Spisák; Vojtech Vancura; Daniel Bohunek; Rodrigo Alves; Pavel Kordík (CoRR, 2025)