A large-scale benchmark finds that in-domain fine-tuning works best for foundation model recommenders, while cross-dataset and multi-domain training help in new scenarios.
Language models as recommender systems: Evalua- tions and limitations
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Evaluating Recabilities of Foundation Models: A Multi-Domain, Multi-Dataset Benchmark
A large-scale benchmark finds that in-domain fine-tuning works best for foundation model recommenders, while cross-dataset and multi-domain training help in new scenarios.