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CALRec: Contrastive Alignment of Generative LLMs For Sequential Recommendation
Building upon the success of Large Language Models (LLMs) in a variety of tasks, researchers have recently explored using LLMs that are pretrained on vast corpora of text for sequential recommendation.
Fast Modeling and Understanding Fluid Dynamics Systems with Encoder-Decoder Networks
The network can be trained within minutes using limited training data and achieve accuracy that scales desirably with the amount of training data supplied.
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