Copertina

Semantic-Enhanced Time-Series Forecasting via Large Language Models

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Liu, Hao, Zhang, Xiaoxing, Yang, Chun, Zhu, Xiaobin
Natura:	Preprint
Pubblicazione:	2025
Soggetti:	Machine Learning Computational Engineering, Finance, and Science
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

FinTSB: A Comprehensive and Practical Benchmark for Financial Time Series Forecasting
di: Hu, Yifan, et al.
Pubblicazione: (2025)

StockTime: A Time Series Specialized Large Language Model Architecture for Stock Price Prediction
di: Wang, Shengkun, et al.
Pubblicazione: (2024)

Leveraging Time Series Categorization and Temporal Fusion Transformers to Improve Cryptocurrency Price Forecasting
di: Peik, Arash, et al.
Pubblicazione: (2024)

Proactive Model Adaptation Against Concept Drift for Online Time Series Forecasting
di: Zhao, Lifan, et al.
Pubblicazione: (2024)

ChatMol: A Versatile Molecule Designer Based on the Numerically Enhanced Large Language Model
di: Fan, Chuanliu, et al.
Pubblicazione: (2025)

Ada-MoGE: Adaptive Mixture of Gaussian Expert Model for Time Series Forecasting
di: Ni, Zhenliang, et al.
Pubblicazione: (2025)

Scale-Equivariant Generative Forecasting: Weight-Tied Dilated Convolutions, Wavelet Scattering Inputs, and Spectral-Consistency Training for Self-Similar Time Series
di: Morandi, Andrea
Pubblicazione: (2026)

Multi-task Meta Label Correction for Time Series Prediction
di: Yang, Luxuan, et al.
Pubblicazione: (2023)

Are Large Language Models Dynamic Treatment Planners? An In Silico Study from a Prior Knowledge Injection Angle
di: Luo, Zhiyao, et al.
Pubblicazione: (2025)

Time Series Analysis in Frequency Domain: A Survey of Open Challenges, Opportunities and Benchmarks
di: Zhang, Qianru, et al.
Pubblicazione: (2025)

FETS Benchmark: Foundation Models Outperform Dataset-specific Machine Learning in Energy Time Series Forecasting
di: Obermeier, Marco, et al.
Pubblicazione: (2026)

Fine-Tuning Pre-trained Large Time Series Models for Prediction of Wind Turbine SCADA Data
di: Fan, Yuwei, et al.
Pubblicazione: (2024)

HKGAI-V1: Towards Regional Sovereign Large Language Model for Hong Kong
di: Han, Sirui, et al.
Pubblicazione: (2025)

Large and Deep Factor Models
di: Kelly, Bryan, et al.
Pubblicazione: (2024)

Using Large Language Models for Parametric Shape Optimization
di: Zhang, Xinxin, et al.
Pubblicazione: (2024)

MemKD: Memory-Discrepancy Knowledge Distillation for Efficient Time Series Classification
di: Udayangani, Nilushika, et al.
Pubblicazione: (2026)

ResNLS: An Improved Model for Stock Price Forecasting
di: Jia, Yuanzhe, et al.
Pubblicazione: (2023)

Transformers with Attentive Federated Aggregation for Time Series Stock Forecasting
di: Thwal, Chu Myaet, et al.
Pubblicazione: (2024)

A Domain Adaptation of Large Language Models for Classifying Mechanical Assembly Components
di: Elhambakhsh, Fatemeh, et al.
Pubblicazione: (2025)

Parametric Nonlinear Volterra Series via Machine Learning: Transonic Aerodynamics
di: Immordino, Gabriele, et al.
Pubblicazione: (2024)

MDAgent2: Large Language Model for Code Generation and Knowledge Q&A in Molecular Dynamics
di: Shi, Zhuofan, et al.
Pubblicazione: (2026)

MolEdit: Knowledge Editing for Multimodal Molecule Language Models
di: Lei, Zhenyu, et al.
Pubblicazione: (2025)

CAMEF: Causal-Augmented Multi-Modality Event-Driven Financial Forecasting by Integrating Time Series Patterns and Salient Macroeconomic Announcements
di: Zhang, Yang, et al.
Pubblicazione: (2025)

Calibrating Scientific Foundation Models with Inference-Time Stochastic Attention
di: Yadav, Akash, et al.
Pubblicazione: (2026)

TransDiffSBDD: Causality-Aware Multi-Modal Structure-Based Drug Design
di: Hu, Xiuyuan, et al.
Pubblicazione: (2025)

3DMolFormer: A Dual-channel Framework for Structure-based Drug Discovery
di: Hu, Xiuyuan, et al.
Pubblicazione: (2025)

ESM All-Atom: Multi-scale Protein Language Model for Unified Molecular Modeling
di: Zheng, Kangjie, et al.
Pubblicazione: (2024)

A Machine Learning Approach For Bitcoin Forecasting
di: Sossi-Rojas, Stefano, et al.
Pubblicazione: (2025)

Unified Network-Based Representation of BIM Models for Embedding Semantic, Spatial, and Topological Data
di: Han, Jin, et al.
Pubblicazione: (2025)

Practical Forecasting of Cryptocoins Timeseries using Correlation Patterns
di: De Rosa, Pasquale, et al.
Pubblicazione: (2024)

Real-Time Online Stock Forecasting Utilizing Integrated Quantitative and Qualitative Analysis
di: Bathini, Sai Akash, et al.
Pubblicazione: (2023)

Generative Large-Scale Pre-trained Models for Automated Ad Bidding Optimization
di: Lei, Yu, et al.
Pubblicazione: (2025)

Operator Learning for Reconstructing Flow Fields from Sparse Measurements: a Language Model Approach
di: Zhang, Qian, et al.
Pubblicazione: (2026)

FHRFormer: A Self-Supervised Masked Transformer Framework for Fetal Heart Rate Time-Series Inpainting and Forecasting
di: Engan, Kjersti, et al.
Pubblicazione: (2026)

Movement Prediction-Adjusted Naive Forecast: Is the Naive Baseline Unbeatable in Financial Time Series Forecasting?
di: Zhang, Cheng
Pubblicazione: (2024)

Diabetica: Adapting Large Language Model to Enhance Multiple Medical Tasks in Diabetes Care and Management
di: Wei, Lai, et al.
Pubblicazione: (2024)

A Novel Decision Ensemble Framework: Customized Attention-BiLSTM and XGBoost for Speculative Stock Price Forecasting
di: Din, Riaz Ud, et al.
Pubblicazione: (2024)

CTBench: Cryptocurrency Time Series Generation Benchmark
di: Ang, Yihao, et al.
Pubblicazione: (2025)

De novo Drug Design using Reinforcement Learning with Multiple GPT Agents
di: Hu, Xiuyuan, et al.
Pubblicazione: (2023)

Empirical Evidence for the Fragment level Understanding on Drug Molecular Structure of LLMs
di: Hu, Xiuyuan, et al.
Pubblicazione: (2024)