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cs.IR2026
Verifiable User Simulation for Search and Recommendation Systems
Chenglong Ma, Xinye Wanyan, Danula Hettiachchi +3
Large-language-model (LLM) based user simulation is increasingly adopted for evaluating search engines, recommender systems, and retrieval-augmented generation pipelines, yet most…
cs.IR2025
Diversity-Augmented Negative Sampling for Implicit Collaborative Filtering
Yueqing Xuan, Kacper Sokol, Mark Sanderson +1
Recommenders built upon implicit collaborative filtering are typically trained to distinguish between users' positive and negative preferences. When direct observations of the latt…