Article

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 …
Cite DOI
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 …
Cite DOI
A Survey on Knowledge-Oriented Retrieval-Augmented Generation
Retrieval-Augmented Generation (RAG) has gained significant attention in recent years for its potential to enhance natural language …
Cite DOI
Advancing Time Series Classification with Multimodal Language Modeling
For the advancements of time series classification, scrutinizing previous studies, most existing methods adopt a common …
Cite DOI
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 …
Cite DOI
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 …
Cite DOI
BLADE: A Behavior-Level Data Augmentation Framework with Dual Fusion Modeling for Multi-Behavior Sequential Recommendation
Multi-behavior sequential recommendation aims to capture users’ dynamic interests by modeling diverse types of user interactions …
Cite DOI
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 …
Cite DOI
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 …
Cite DOI
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 …
Cite DOI