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Sponsored Design Multi-Agent AI Systems Using MCP and A2A: Engineer your own Pyt Design Multi-Agent AI Systems Using MCP and A2A: Engineer your own Pyt

Author

Ladislav Peška

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Book Open access Sep 2026

Candidate Retrieval for Provider Fairness under Severe Recommendation Imbalance

Provider fairness in recommender systems is commonly addressed through reranking, which assumes that the candidate set already contains sufficient items from under-exposed provider groups. We study a setting in which this assumption breaks down: catalog representation does not translate into recommendation exposure, an...

Patrik Dokoupil, L. Boratto, Ladislav Peška · 0 citations
Book Open access Sep 2026

Sparse Autoencoders as Semantic Domain Adapters for Recommender Systems

Pretrained text embeddings enable content-based cold-item recommendation, but their domain-agnostic objectives may underrepresent distinctions that matter within a particular recommendation domain. We investigate lightweight autoencoder adapters that specialize these embeddings without retraining or finetuning the embe...

Vojtěch Vančura, G. Medda, Martin Spišák et al. · 0 citations

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