Mar 27, 2024 · In this paper, we propose a novel relation-aware sequential recommendation framework with Latent Relation Discovery (LRD).
Jul 14, 2024 · Sequential recommender systems predict items that may interest users by modeling their preferences based on historical interactions. Traditional ...
This is the official implementation for Sequential Recommendation with Latent Relations based on Large Language Model.
Jul 14, 2024 · Sequential recommender system (SRS) predicts the next items that users may prefer based on user historical interaction sequences. Inspired by ...
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This is a paper list about Large Language Model-enhanced Recommender System. It also contains some related works.
We first use a large language model (LLM) to construct personalized reasoning graphs based on Su and. Au, which reason a user's profile and behavioral sequences.
Oct 31, 2023 · Sequential recommendation is to predict the next item of interest for a user, based on her/his interaction history with previous items.
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This is because recommender systems typically require low latency for online deployment, whereas LLMs often entail high inference costs [19]. ii) Deficiency ...
Jun 28, 2024 · We consider it to be right the time to review the challenges in personalization and the opportunities to address them with large language models.
Sep 1, 2024 · Recent advancements in sequential recommendation involve the use of large language models (LLMs) to discover latent relations between items. The ...