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Found 4 papers, 2 papers with code
RecFusion: A Binomial Diffusion Process for 1D Data for Recommendation
In this paper we propose RecFusion, which comprise a set of diffusion models for recommendation.
Gen-IR @ SIGIR 2023: The First Workshop on Generative Information Retrieval
Generative information retrieval (IR) has experienced substantial growth across multiple research communities (e. g., information retrieval, computer vision, natural language processing, and machine learning), and has been highly visible in the popular press.
RADio -- Rank-Aware Divergence Metrics to Measure Normative Diversity in News Recommendations
In traditional recommender system literature, diversity is often seen as the opposite of similarity, and typically defined as the distance between identified topics, categories or word models.
sigmoidF1: A Smooth F1 Score Surrogate Loss for Multilabel Classification
We propose a loss function, sigmoidF1, which is an approximation of the F1 score that (1) is smooth and tractable for stochastic gradient descent, (2) naturally approximates a multilabel metric, and (3) estimates label propensities and label counts.
