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arxiv.org
http://arxiv.org > abs > 2509.02220v1
Towards Multi-Aspect Diversification of News Recommendations Using Neuro-Symbolic AI for Individual and Societal Benefit
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arxiv.org
http://arxiv.org > abs > 2508.17571v1
A Universal Framework for Offline Serendipity Evaluation in Recommender Systems via Large Language Models
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arxiv.org
http://arxiv.org > abs > 2508.06569v1
Operationalizing Serendipity: Multi-Agent AI Workflows for Enhanced Materials Characterization with Theory-in-the-Loop
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arxiv.org
http://arxiv.org > abs > 2508.04032v1
Enhancing Serendipity Recommendation System by Constructing Dynamic User Knowledge Graphs with Large Language Models
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arxiv.org
http://arxiv.org > abs > 2507.17290v1
Exploring the Potential of LLMs for Serendipity Evaluation in Recommender Systems
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arxiv.org
http://arxiv.org > abs > 2506.21617v1
Bayesian-Guided Diversity in Sequential Sampling for Recommender Systems
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arxiv.org
http://arxiv.org > abs > 2506.08283v2
Serendipitous Recommendation with Multimodal LLM
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arxiv.org
http://arxiv.org > abs > 2505.24652v2
Chasing Serendipity: Tackling Transient Sources with Neutrino Telescopes
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arxiv.org
http://arxiv.org > abs > 2505.23580v1
Engineering Serendipity through Recommendations of Items with Atypical Aspects
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arxiv.org
http://arxiv.org > abs > 2505.15440v1
What Is Serendipity? An Interview Study to Conceptualize Experienced Serendipity in Recommender Systems