Awesome Foundation Models

Key papers

• LLM4TS: Aligning Pre-Trained LLMs as Data-Efficient Time-Series Forecasters (2023)
  Ching Chang et al.
  14.28
• Deep Time Series Models: A Comprehensive Survey and Benchmark (2024)
  Yuxuan Wang et al.
  13.40
• Chronos-2: From Univariate to Universal Forecasting (2025)
  Abdul Fatir Ansari et al.
  11.41
• Time-VLM: Exploring Multimodal Vision-Language Models for Augmented Time Series Forecasting (2025)
  Siru Zhong et al.
  10.54
• Multi-modal Time Series Analysis: A Tutorial and Survey (2025)
  Yushan Jiang et al.
  10.40
• LangTime: A Language-Guided Unified Model for Time Series Forecasting with Proximal Policy Optimization (2025)
  Wenzhe Niu et al.
  8.67
• fev-bench: A Realistic Benchmark for Time Series Forecasting (2025)
  Oleksandr Shchur et al.
  8.16
• ChronosX: Adapting Pretrained Time Series Models with Exogenous Variables (2025)
  Sebastian Pineda Arango et al.
  7.95
• From Values to Tokens: An LLM-Driven Framework for Context-aware Time Series Forecasting via Symbolic Discretization (2025)
  Xiaoyu Tao et al.
  7.68
• Time-Series Foundation Model Embeddings for Remaining Useful Life Estimation (2026)
  Amir El-Ghoussani et al.
  7.37
• Looped World Models (2026)
  Hongyuan Adam Lu et al.
  7.37
• Aurora: Towards Universal Generative Multimodal Time Series Forecasting (2025)
  Xingjian Wu et al.
  7.22
• Kronos: A Foundation Model for the Language of Financial Markets (2025)
  Yu Shi et al.
  7.17
• FinCast: A Foundation Model for Financial Time-Series Forecasting (2025)
  Zhuohang Zhu et al.
  7.17
• Empowering Time Series Forecasting with LLM-Agents (2025)
  Chin-Chia Michael Yeh and Vivian Lai and Uday Singh Saini and Xiran Fan and Yujie Fan and Junpeng Wang and Xin Dai and Yan Zheng
  6.75
• Vision-Enhanced Time Series Forecasting via Latent Diffusion Models (2025)
  Weilin Ruan et al.
  6.63
• Panda: A pretrained forecast model for chaotic dynamics (2025)
  Jeffrey Lai et al.
  6.58
• FlowState: Sampling Rate Invariant Time Series Forecasting (2025)
  Lars Graf et al.
  6.51
• Time-MoE: Billion-Scale Time Series Foundation Models with Mixture of Experts (2024)
  Xiaoming Shi et al.
  6.36
• Enhancing Time Series Forecasting via Multi-Level Text Alignment with LLMs (2025)
  Taibiao Zhao et al.
  6.01
• Large Language Models for Mobility Analysis in Transportation Systems: A Survey on Forecasting Tasks (2024)
  Zijian Zhang et al.
  5.91
• TempoPFN: Synthetic Pre-training of Linear RNNs for Zero-shot Time Series Forecasting (2025)
  Vladyslav Moroshan and Julien Siems and Arber Zela and Timur Carstensen and Frank Hutter
  5.68
• TimeCAP: Learning to Contextualize, Augment, and Predict Time Series Events with Large Language Model Agents (2025)
  Geon Lee et al.
  5.59
• Using Pre-trained LLMs for Multivariate Time Series Forecasting (2025)
  Malcolm L. Wolff et al.
  5.54
• TempoGPT: Enhancing Time Series Reasoning via Quantizing Embedding (2025)
  Haochuan Zhang et al.
  5.54
• EHRNote-ChatQA: A Benchmark for Evidence-Grounded Multi-Turn Clinical Question Answering over Longitudinal Discharge Summaries (2026)
  Jiyoun Kim et al.
  5.49
• Public transit gains and spatially uneven travel demand changes after NYC congestion pricing (2026)
  Donghang Li et al.
  5.49
• Efficient Multivariate Time Series Forecasting via Calibrated Language Models with Privileged Knowledge Distillation (2025)
  Chenxi Liu et al.
  5.40
• ST-MTM: Masked Time Series Modeling with Seasonal-Trend Decomposition for Time Series Forecasting (2025)
  Hyunwoo Seo and Chiehyeon Lim
  5.10
• LLM Features Can Hurt GNNs: Concatenation Interference on Homophilous Graph Benchmarks (2026)
  Zhongyuan Wang et al.
  5.01
• LLM Consumer Behavior Theory: Foundations of a Novel Research Field (2026)
  Manon Reusens et al.
  5.01
• Your AI Travel Agent Would Book You a Bullfight: An Agentic Benchmark for Implicit Animal Welfare in Frontier AI Models (2026)
  Jasmine Brazilek et al.
  5.01
• Towards Cross-Modality Modeling for Time Series Analytics: A Survey in the LLM Era (2025)
  Chenxi Liu et al.
  4.98
• Forging Time Series with Language: A Large Language Model Approach to Synthetic Data Generation (2025)
  C\'ecile Rousseau et al.
  4.98
• TimeSeriesScientist: A General-Purpose AI Agent for Time Series Analysis (2025)
  Haokun Zhao et al.
  4.90
• Crime Forecasting: A Spatio-temporal Analysis with Deep Learning Models (2025)
  Li Mao et al.
  4.82
• From Tables to Time: Extending TabPFN-v2 to Time Series Forecasting (2025)
  Shi Bin Hoo et al.
  4.76
• Unveiling the Potential of Text in High-Dimensional Time Series Forecasting (2025)
  Xin Zhou and Weiqing Wang and Shilin Qu and Zhiqiang Zhang and Christoph Bergmeir
  4.76
• Joint Embeddings Go Temporal (2025)
  Sofiane Ennadir et al.
  4.69
• CALF: Aligning LLMs for Time Series Forecasting via Cross-modal Fine-Tuning (2024)
  Peiyuan Liu et al.
  4.63
• Foundation Models for Demand Forecasting via Dual-Strategy Ensembling (2025)
  Wei Yang et al.
  4.58
• Benchmarking Pre-Trained Time Series Models for Electricity Price Forecasting (2025)
  Timoth\'ee Hornek Amir Sartipi and Igor Tchappi and Gilbert Fridgen
  4.53
• Generalisation Bounds of Zero-Shot Economic Forecasting using Time Series Foundation Models (2025)
  Jittarin Jetwiriyanon et al.
  4.53
• How Effective are Large Time Series Models in Hydrology? A Study on Water Level Forecasting in Everglades (2025)
  Rahuul Rangaraj et al.
  4.47
• Explainable and Interpretable Forecasts on Non-Smooth Multivariate Time Series for Responsible Gameplay (2025)
  Hussain Jagirdar et al.
  4.42
• Forecasting Clinical Risk from Textual Time Series: Structuring Narratives for Temporal AI in Healthcare (2025)
  Shahriar Noroozizadeh et al.
  4.42
• Bridging Distribution Gaps in Time Series Foundation Model Pretraining with Prototype-Guided Normalization (2025)
  Peiliang Gong et al.
  4.42
• Discovering Functionally Selective Brain Regions with a Deep Topographic Multimodal Model (2026)
  Badr AlKhamissi et al.
  4.39
• CITRAS-FM: Tiny Time Series Foundation Model for Covariate-Informed Zero-Shot Forecasting (2026)
  Yosuke Yamaguchi et al.
  4.39
• LakeFM: Toward a Foundation Model for Aquatic Ecosystems Using Irregular Multivariate Multi-depth Time Series Data (2026)
  Abhilash Neog et al.
  4.39
• Medical Heuristic Learning: An LLM-Driven Framework for Interpretable and Auditable Clinical Decision Rules (2026)
  Wei Xu et al.
  4.39
• Comprehensive pKa Data Augmentation from Limited Real Data through an Engineered Models-Quantum Framework (2026)
  Wang Rui et al.
  4.39
• Quantum Cinema: An Interactive Cinematic Exploration of Quantum Computing Hardware via Generative World Models (2026)
  Aoyu Zhang et al.
  4.39
• Informative Missingness to Generate Irregular Clinical Time Series (2026)
  Hadi Mehdizavareh et al.
  4.39
• Models Take Notes at Prefill: KV Cache Can Be Editable and Composable (2026)
  Bojie Li
  4.39
• Loss Landscape Poisoning: Targeted Extraction of Unseen Training Data from LLMs (2026)
  Md Abdullah Al Mamun et al.
  4.39
• The Critical Role of Model Selection in Causal Inference: A Comparative Analysis of Classification Models within the InferBERT Framework for Pharmacovigilance (2026)
  Csaba Kiss et al.
  4.39
• Probing, Fusion, and Trustworthiness: A Systematic Evaluation of Foundation Model Representations for Multimodal Cancer Analysis (2026)
  Jingyu Hu et al.
  4.39
• Statistical Foundations of LLM-based A/B Testing: A Surrogacy Framework for Human Causal Inference (2026)
  Joel Persson et al.
  4.39
• Constrained Diffusion Models with Primal-Dual Inference (2026)
  Samar Hadou et al.
  4.39