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Rethinking Large Language Model Architectures for Sequential Recommendations
This design stems from our empirical observation that beam search decoding is ultimately unnecessary for sequential recommendations.
Hebbian Graph Embeddings
Representation learning has recently been successfully used to create vector representations of entities in language learning, recommender systems and in similarity learning.
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