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Awesome-Large-Models-for-Time-Series

SOTA

Venue Title
Under review of ICLR'25 Time-MoE: Billion-Scale Time Series Foundation Models with Mixture of Experts
Under review of ICLR'25 In-context Time Series Predictor
NIPS'24 SOFTS: Efficient Multivariate Time Series Forecasting with Series-Core Fusion
NIPS'24 Are Self-Attentions Effective for Time Series Forecasting?

Survey

Venue Title
ICML'24 Position: What Can Large Language Models Tell Us about Time Series Analysis
KDD'24 Foundation Models for Time Series Analysis: A Tutorial and Survey

Benchmark

Venue Title Keywords
Under Review of ICLR'25 FoundTS: Comprehensive and Unified Benchmarking of Foundation Models for Time Series Forecasting
Under Review of ICLR'25 GIFT-Eval: A Benchmark for General Time Series Forecasting Model Evaluation

Training

Pretrained Foundation Models

Venue Title Keywords
Under Review of ICLR'25 Moirai-MoE: Empowering Time Series Foundation Models with Sparse Mixture of Experts
Under Review of ICLR'25 FlexTSF: A universal forecasting model for time series with variable regularities
Under Review of ICLR'25 Towards Generalisable Time Series Understanding Across Domains
NIPS'24 Large Pre-trained time series models for cross-domain Time series analysis tasks
NIPS’24 UNITS: A Unified Multi-Task Time Series Model One model for many tasks; Prompt tuning
ICML'24 Unified Training of Universal Time Series Forecasting Transformers Multivariate; Large-scale data; Variable window size
ICML’24 Timer: Generative Pre-trained Transformers Are Large Time Series Models Channel independence; Large-scale data; Auto-regression
ICML'24 MOMENT: A Family of Open Time-series Foundation Models Masked auto-encoder pretraining
ICML'24 A decoder-only foundation model for time-series forecasting Auto-regressive patch-wise decoding

Special Designs

Venue Title Keywords
Under Review of ICLR'25 Enhancing Foundation Models for Time Series Forecasting via Wavelet-based Tokenization
Under Review of ICLR'25 Towards Adaptive Time Series Foundation Models Against Distribution Shift

Fine-Tuning

Venue Title Keywords
Under Review of ICLR'25 In-context Fine-tuning for Time-series Foundation Models
Under Review of ICLR'25

Pre-Training & Fine-Tuning

Venue Title Keywords
ICML'24 UP2ME: Univariate Pre-training to Multivariate Fine-tuning as a General-purpose Framework for Multivariate Time Series Analysis Masked auto-encoder pretraining; Variable window size; Multivariate fine-tuning
ICML'24 Multi-Patch Prediction: Adapting LLMs for Time Series Representation Learning Autoregressive patch-wise decoding

Prompting / Conditional Generation

Venue Title Keywords
Under Review of ICLR'25 TimeRAF: Retrieval-Augmented Foundation model for Zero-shot Time Series Forecasting
Under Review of ICLR'25 TimeRAG: It's Time for Retrieval-Augmented Generation in Time-Series Forecasting
Under Review of ICLR'25 Retrieval Augmented Time Series Forecasting
Under Review of ICLR'25 CRAFT: Time Series Forecasting with Cross-Future Behavior Awareness
Under Review of ICLR'25 Metadata Matters for Time Series: Informative Forecasting with Transformers
ICML'24 Time Weaver: A Conditional Time Series Generation Model Diffusion
ICML'24 S$^2$IP-LLM: Semantic Space Informed Prompt Learning with LLM for Time Series Forecasting Retrieve word embeddings
KDD'24 POND: Multi-Source Time Series Domain Adaptation with Information-Aware Prompt Tuning Transfer

Long-context

Venue Title Keywords
Under Review of ICLR'25 Timer-XL: Long-Context Transformers for Unified Time Series Forecasting

Misc

Lightweight

Venue Title Keywords
Under Review of ICLR'25 FastTF: 4 Parameters are All You Need for Long-term Time Series Forecasting
ICML'24 SparseTSF: Modeling Long-term Time Series Forecasting with 1k Parameters

Non-stationary

Venue Title Keywords
ICML'24 SIN: Selective and Interpretable Normalization for Long-Term Time Series Forecasting

Multi-Modal

Venue Title Keywords
NIPS'24 Time-MMD: A New Multi-Domain Multimodal Dataset for Time Series Analysis
MoAT: Multi-Modal Augmented Time Series Forecasting News article

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Papers for LLM and foundation models for time series analytics

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