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Development and Validation of a Lightweight DeepFM Model with Attention-Driven Feature Selection and Meta-Learning Tuning

https://doi.org/10.2139/ssrn.5341192
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Outgoing claims: the papers this work cites, builds on, or argues with.

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Tapping the Potential of Large Language Models as Recommender Systems: A Comprehensive Framework and Empirical Analysis
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Graph Neural Networks for Tabular Data Learning: A Survey with Taxonomy and Directions
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Embedding in Recommender Systems: A Survey
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