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Advancing Time Series Classification with Multimodal Language Modeling
For the advancements of time series classification, scrutinizing previous studies, most existing methods adopt a common …
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Learning Transferable Time Series Classifier with Cross-Domain Pre-training from Language Model
Advancements in self-supervised pre-training (SSL) have significantly advanced the field of learning transferable time series …
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ConvTimeNet: A Deep Hierarchical Fully Convolutional Model for Multivariate Time Series Analysis
This paper introduces ConvTimeNet, a novel deep hierarchical fully convolutional network designed to serve as a general-purpose model …
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Generative Pretrained Hierarchical Transformer for Time Series Forecasting
Recent efforts have been dedicated to enhancing time series forecasting accuracy by introducing advanced network architectures and …
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Unlocking the Potential of Large Language Models for Explainable Recommendations
Generating user-friendly explanations regarding why an item is recommended has become increasingly common, largely due to advances in …
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Towards Automatic Sampling of User Behaviors for Sequential Recommender Systems
Sequential recommender systems (SRS) have gained widespread popularity in recommendation due to their ability to effectively capture …
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A survey on large language models for recommendation
Large Language Models (LLMs) have emerged as powerful tools in the field of Natural Language Processing (NLP) and have recently gained …
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TimeMAE: Self-Supervised Representations of Time Series with Decoupled Masked Autoencoders
Enhancing the expressive capacity of deep learning-based time series models with self-supervised pre-training has become …
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