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Preference Trajectory Modeling via Flow Matching for Sequential Recommendation
Sequential recommendation predicts each user’s next item based on their historical interaction sequence. Recently, diffusion …
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Time Series Forecasting as Reasoning: A Slow-Thinking Approach with Reinforced LLMs
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Are LLMs Stable Formal Logic Translators in Logical Reasoning Across Linguistically Diversified Texts?
Logical reasoning with large language models (LLMs) has received growing attention. One mainstream approach translates natural language …
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A Comprehensive Survey of Time Series Forecasting: Concepts, Challenges, and Future Directions
Time series forecasting (TSF) has become an increasingly vital tool in various decision-making applications, including business …
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A Survey on Table Mining with Large Language Models: Challenges, Advancements and Prospects
Table mining is a popular research field that involves complicated technologies, including information retrieval, data mining, visual …
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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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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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