awesome-spatiotemporal-LMMs

Survey or Vision Paper

1. Large Models for Time Series and Spatio-Temporal Data: A Survey and Outlook, arXiv 2023.10, paper, repo
2. Towards Graph Foundation Models: A Survey and Beyond, arXiv 2023.10, paper, repo
3. A Survey of Deep Learning and Foundation Models for Time Series Forecasting, arXiv 2024.01, paper
4. Large Language Models for Time Series: A Survey, arXiv 2024.02, paper, repo
5. Empowering Time Series Analysis with Large Language Models: A Survey, arXiv 2024.02, paper
6. Graph Foundation Models, arXiv 2024.02, paper, repo
7. Large Language Models for Forecasting and Anomaly Detection: A Systematic Literature Review, arXiv 2024.02, paper
8. Towards Urban General Intelligence: A Review and Outlook of Urban Foundation Model, arXiv 2024.02, paper, repo
9. On the Opportunities and Challenges of Foundation Models for GeoAI, ACM Transactions on Spatial Algorithms and Systems 24.03, paper
10. Foundation Models for Time Series Analysis: A Tutorial and Survey, arXiv 2024.03, paper

Research Paper

1. Leveraging Language Foundation Models for Human Mobility Forecasting, SIGSPATIAL 2022, paper
2. ERNIE-GeoL: A Geography-and-Language Pre-trained Model and its Applications in Baidu Maps, KDD 2022, paper
3. PromptCast: A New Prompt-based Learning Paradigm for Time Series Forecasting, TKDE 2023, paper, repo
4. G2PTL: A Pre-trained Model for Delivery Address and its Applications in Logistics System, arXiv 2023.04
5. Where Would I Go Next? Large Language Models as Human Mobility Predictors, arXiv 2023.08
6. TrafficGPT: Viewing, Processing and Interacting with Traffic Foundation Models, arXiv 2023.09
7. Penetrative AI: Making LLMs Comprehend the Physical World, arXiv 2023.10
8. Large Language Models for Spatial Trajectory Patterns Mining, arXiv 2023.10
9. Large Language Models Are Zero-Shot Time Series Forecasters, NeurIPS 2023
10. One Fits All:Power General Time Series Analysis by Pretrained LM, arXiv 2023.10
11. TimeGPT-1, arXiv 2023.10
12. TEMPO: Prompt-based Generative Pre-trained Transformer for Time Series Forecasting, arXiv 2023.10
13. MGeo: Multi-Modal Geographic Language Model Pre-Training, SIGIR 2023
14. TEST: Text Prototype Aligned Embedding to Activate LLM's Ability for Time Series, ICLR 2024
15. Time-LLM: Time Series Forecasting by Reprogramming Large Language Models, ICLR 2024
16. UniTime: A Language-Empowered Unified Model for Cross-Domain Time Series Forecasting, WWW 2024
17. Spatial-Temporal Large Language Model for Traffic Prediction, arXiv 2024.01
18. How Can Large Language Models Understand Spatial-Temporal Data? arXiv 2024.01
19. LLM4TS: Aligning Pre-Trained LLMs as Data-Efficient Time-Series Forecasters, arXiv 2024.01
20. UniST: A Prompt-Empowered Universal Model for Urban Spatio-Temporal Prediction, arXiv 2024.02
21. Position Paper: What Can Large Language Models Tell Us about Time Series Analysis, arXiv 2024.02
22. Lag-Llama: Towards Foundation Models for Probabilistic Time Series Forecasting, arXiv 2024.02
23. GeoLLM: Extracting Geospatial Knowledge from Large Language Models, arXiv 2024.02
24. Beyond Imitation: Generating Human Mobility from Context-aware Reasoning with Large Language Models, arXiv 2024.02
25. Large Language Models as Urban Residents: An LLM Agent Framework for Personal Mobility Generation, arXiv 2024.02
26. Semantic understanding and prompt engineering for large-scale traffic data imputation, Information Fusion 24.02, paper
27. UrbanKGent: A Unified Large Language Model Agent Framework for Urban Knowledge Graph Construction, arXiv 2024.02
28. UrbanVLP: A Multi-Granularity Vision-Language Pre-Trained Foundation Model for Urban Indicator Prediction, arXiv 24.03
29. UniTS: Building a Unified Time Series Model, arXiv 2024.03
30. Chronos: Learning the Language of Time Series, arXiv 2024.03
31. TPLLM: A Traffic Prediction Framework Based on Pretrained Large Language Models, arXiv 2024.03
32. S2IP-LLM: Semantic Space Informed Prompt Learning with LLM for Time Series Forecasting, arXiv 2024.03
33. UrbanGPT: Spatio-Temporal Large Language Models, arXiv 24.03
34. LG-Traj: LLM Guided Pedestrian Trajectory Prediction, arXiv 24.03