3 papers
cs.IR2026
Diagnosing LLM-based Rerankers in Cold-Start Recommender Systems: Coverage, Exposure and Practical Mitigations
Ekaterina Lemdiasova, Nikita Zmanovskii
Large language models (LLMs) and cross-encoder rerankers have gained attention for improving recommender systems, particularly in cold-start scenarios where user interaction histor…
cs.CL2026
Combating data scarcity in recommendation services: Integrating cognitive types of VARK and neural network technologies (LLM)
Nikita Zmanovskii
Cold start scenarios present fundamental obstacles to effective recommendation generation, particularly when dealing with users lacking interaction history or items with sparse met…
cs.CL2025
Qwerty AI: Explainable Automated Age Rating and Content Safety Assessment for Russian-Language Screenplays
Nikita Zmanovskii
We present Qwerty AI, an end-to-end system for automated age-rating and content-safety assessment of Russian-language screenplays according to Federal Law No. 436-FZ. The system pr…