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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.
Investigating Meta-Learning Algorithms for Low-Resource Natural Language Understanding Tasks
Learning general representations of text is a fundamental problem for many natural language understanding (NLU) tasks.
Fast and Accurate Text Classification: Skimming, Rereading and Early Stopping
Recent advances in recurrent neural nets (RNNs) have shown much promise in many applications in natural language processing.
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