{"total":208,"rows":[{"id":"2402.03885","title":"MOMENT: A Family of Open Time-series Foundation Models","created":"2024-02-06","cited_by_count":482,"area":null},{"id":"2409.16040","title":"Time-MoE: Billion-Scale Time Series Foundation Models with Mixture of Experts","created":"2024-09-24","cited_by_count":287,"area":"moe"},{"id":"2502.00816","title":"Sundial: A Family of Highly Capable Time Series Foundation Models","created":"2025-02-02","cited_by_count":180,"area":null},{"id":"2410.10469","title":"Moirai-MoE: Empowering Time Series Foundation Models with Sparse Mixture of Experts","created":"2024-10-14","cited_by_count":95,"area":"moe"},{"id":"2408.17253","title":"VisionTS: Visual Masked Autoencoders Are Free-Lunch Zero-Shot Time Series Forecasters","created":"2024-08-30","cited_by_count":88,"area":null},{"id":"2410.04803","title":"Timer-XL: Long-Context Transformers for Unified Time Series Forecasting","created":"2024-10-07","cited_by_count":87,"area":null},{"id":"2503.01875","title":"Time-MQA: Time Series Multi-Task Question Answering with Context Enhancement","created":"2025-02-26","cited_by_count":82,"area":null},{"id":"2406.08627","title":"Time-MMD: Multi-Domain Multimodal Dataset for Time Series Analysis","created":"2024-06-12","cited_by_count":74,"area":null},{"id":"2505.14766","title":"This Time is Different: An Observability Perspective on Time Series Foundation Models","created":"2025-05-20","cited_by_count":68,"area":null},{"id":"2502.10721","title":"A Comprehensive Survey of Deep Learning for Multivariate Time Series Forecasting: A Channel Strategy Perspective","created":"2025-02-15","cited_by_count":58,"area":null},{"id":"2402.04059","title":"Deep Learning for Multivariate Time Series Imputation: A Survey","created":"2024-02-06","cited_by_count":57,"area":null},{"id":"2410.14752","title":"TimeSeriesExam: A time series understanding exam","created":"2024-10-18","cited_by_count":49,"area":null},{"id":"2510.23672","title":"DBLoss: Decomposition-based Loss Function for Time Series Forecasting","created":"2025-10-27","cited_by_count":45,"area":null},{"id":"2503.07649","title":"TS-RAG: Retrieval-Augmented Generation based Time Series Foundation Models are Stronger Zero-Shot Forecaster","created":"2025-03-06","cited_by_count":40,"area":"rag"},{"id":"2506.20093","title":"ITFormer: Bridging Time Series and Natural Language for Multi-Modal QA with Large-Scale Multitask Dataset","created":"2025-06-25","cited_by_count":37,"area":null},{"id":"2410.12360","title":"Towards Neural Scaling Laws for Time Series Foundation Models","created":"2024-10-16","cited_by_count":33,"area":null},{"id":"2509.22295","title":"Aurora: Towards Universal Generative Multimodal Time Series Forecasting","created":"2025-09-26","cited_by_count":29,"area":null},{"id":"2603.04791","title":"Timer-S1: A Billion-Scale Time Series Foundation Model with Serial Scaling","created":"2026-03-05","cited_by_count":28,"area":"moe"},{"id":"2410.09836","title":"Learning Pattern-Specific Experts for Time Series Forecasting Under Patch-level Distribution Shift","created":"2024-10-13","cited_by_count":24,"area":null},{"id":"2405.02358","title":"Empowering Time Series Analysis with Foundation Models: A Comprehensive Survey","created":"2024-05-03","cited_by_count":23,"area":null},{"id":"2504.04011","title":"Foundation Models for Time Series: A Survey","created":"2025-04-05","cited_by_count":23,"area":null},{"id":"2506.07584","title":"MIRA: Medical Time Series Foundation Model for Real-World Health Data","created":"2025-06-09","cited_by_count":22,"area":null},{"id":"2409.12915","title":"Exploring Representations and Interventions in Time Series Foundation Models","created":"2024-09-19","cited_by_count":20,"area":null},{"id":"2501.06907","title":"Deep Learning and Foundation Models for Weather Prediction: A Survey","created":"2025-01-12","cited_by_count":16,"area":null},{"id":"2503.13868","title":"Out-of-Distribution Generalization in Time Series: A Survey","created":"2025-03-18","cited_by_count":16,"area":null},{"id":"2505.17871","title":"BLAST: Balanced Sampling Time Series Corpus for Universal Forecasting Models","created":"2025-05-23","cited_by_count":16,"area":null},{"id":"2510.13654","title":"Rethinking Evaluation in the Era of Time Series Foundation Models: (Un)known Information Leakage Challenges","created":"2025-10-15","cited_by_count":16,"area":"lr"},{"id":"2410.05711","title":"TimeDART: A Diffusion Autoregressive Transformer for Self-Supervised Time Series Representation","created":"2024-10-08","cited_by_count":14,"area":null},{"id":"2412.08906","title":"Federated Foundation Models on Heterogeneous Time Series","created":"2024-12-12","cited_by_count":13,"area":null},{"id":"2508.02879","title":"CauKer: Classification Time Series Foundation Models Can Be Pretrained on Synthetic Data","created":"2025-08-04","cited_by_count":13,"area":"synth"},{"id":"2508.20370","title":"Adaptive Root Cause Localization for Microservice Systems with Multi-Agent Recursion-of-Thought","created":"2025-08-28","cited_by_count":13,"area":"lr"},{"id":"2602.17634","title":"Reverso: Efficient Time Series Foundation Models for Zero-shot Forecasting","created":"2026-02-19","cited_by_count":13,"area":null},{"id":"2508.04379","title":"VisionTS++: Cross-Modal Time Series Foundation Model with Continual Pre-trained Vision Backbones","created":"2025-08-06","cited_by_count":12,"area":null},{"id":"2510.03519","title":"TS-Reasoner: Aligning Time Series Foundation Models with LLM Reasoning","created":"2025-10-03","cited_by_count":12,"area":"lr"},{"id":"2501.15942","title":"TimeHF: Billion-Scale Time Series Models Guided by Human Feedback","created":"2025-01-27","cited_by_count":10,"area":"alignment"},{"id":"2603.26017","title":"QuitoBench: A High-Quality Open Time Series Forecasting Benchmark","created":"2026-03-27","cited_by_count":10,"area":null},{"id":"2605.27286","title":"Falcon-X: A Time Series Foundation Model for Heterogeneous Multivariate Modeling","created":"2026-05-26","cited_by_count":10,"area":null},{"id":"2411.02941","title":"A Mamba Foundation Model for Time Series Forecasting","created":"2024-11-05","cited_by_count":9,"area":"ssm"},{"id":"2505.19090","title":"CMoS: Rethinking Time Series Prediction Through the Lens of Chunk-wise Spatial Correlations","created":"2025-05-25","cited_by_count":9,"area":null},{"id":"2509.00616","title":"TimeCopilot","created":"2025-08-30","cited_by_count":9,"area":"agents"},{"id":"2606.14222","title":"Learning the Context of Errors: Black-Box Online Adaptation of Time Series Foundation Models","created":"2026-06-12","cited_by_count":9,"area":null},{"id":"2502.14045","title":"There are no Champions in Supervised Long-Term Time Series Forecasting","created":"2025-02-19","cited_by_count":8,"area":null},{"id":"2510.22880","title":"Learning Reconfigurable Representations for Multimodal Federated Learning with Missing Data","created":"2025-10-27","cited_by_count":8,"area":null},{"id":"2510.25207","title":"Selective Learning for Deep Time Series Forecasting","created":"2025-10-29","cited_by_count":8,"area":null},{"id":"2506.24124","title":"Teaching Time Series to See and Speak: Forecasting with Aligned Visual and Textual Perspectives","created":"2025-06-30","cited_by_count":7,"area":null},{"id":"2510.16014","title":"STAR: Boosting Time Series Foundation Models for Anomaly Detection through State-aware Adapter","created":"2025-10-15","cited_by_count":7,"area":null},{"id":"2510.19710","title":"SEMPO: Lightweight Foundation Models for Time Series Forecasting","created":"2025-10-22","cited_by_count":7,"area":null},{"id":"2411.12747","title":"A Survey of Financial AI: Architectures, Advances and Open Challenges","created":"2024-11-01","cited_by_count":6,"area":null},{"id":"2506.08641","title":"Unlocking Pretrained Vision Transformers for Time Series Classification","created":"2025-06-10","cited_by_count":6,"area":null},{"id":"2507.08858","title":"Foundation models for time series forecasting: Application in conformal prediction","created":"2025-07-09","cited_by_count":6,"area":null},{"id":"2508.12235","title":"CC-Time: Cross-Model and Cross-Modality Time Series Forecasting","created":"2025-08-17","cited_by_count":6,"area":null},{"id":"2406.14399","title":"Benchmarking Physics-Informed Time-Series Models for Operational Global Station Weather Forecasting","created":"2024-06-20","cited_by_count":5,"area":null},{"id":"2409.10840","title":"Implicit Reasoning in Deep Time Series Forecasting","created":"2024-09-17","cited_by_count":5,"area":"lr"},{"id":"2409.13530","title":"Towards Long-Context Time Series Foundation Models","created":"2024-09-20","cited_by_count":5,"area":null},{"id":"2410.03806","title":"Metadata Matters for Time Series: Informative Forecasting with Transformers","created":"2024-10-04","cited_by_count":5,"area":null},{"id":"2410.23356","title":"Sequential Order-Robust Mamba for Time Series Forecasting","created":"2024-10-30","cited_by_count":5,"area":"ssm"},{"id":"2411.13428","title":"SynEHRgy: Synthesizing Mixed-Type Structured Electronic Health Records using Decoder-Only Transformers","created":"2024-11-20","cited_by_count":5,"area":null},{"id":"2412.15315","title":"Enhancing Masked Time-Series Modeling via Dropping Patches","created":"2024-12-19","cited_by_count":5,"area":null},{"id":"2505.14411","title":"Byte Pair Encoding for Efficient Time Series Forecasting","created":"2025-05-20","cited_by_count":5,"area":null},{"id":"2510.06063","title":"TelecomTS: A Multi-Modal Observability Dataset for Time Series and Language Analysis","created":"2025-10-07","cited_by_count":5,"area":null},{"id":"2603.15452","title":"Unlocking the Value of Text: Event-Driven Reasoning and Multi-Level Alignment for Time Series Forecasting","created":"2026-03-16","cited_by_count":5,"area":"lr"},{"id":"2411.15743","title":"Beyond Data Scarcity: A Frequency-Driven Framework for Zero-Shot Forecasting","created":"2024-11-24","cited_by_count":4,"area":null},{"id":"2412.00395","title":"On Foundation Models for Dynamical Systems from Purely Synthetic Data","created":"2024-11-30","cited_by_count":4,"area":"synth"},{"id":"2502.03264","title":"GTM: A General Time-series Model for Enhanced Representation Learning of Time-Series Data","created":"2025-02-05","cited_by_count":4,"area":null},{"id":"2503.04118","title":"TimeFound: A Foundation Model for Time Series Forecasting","created":"2025-03-06","cited_by_count":4,"area":null},{"id":"2505.20535","title":"Rotary Masked Autoencoders are Versatile Learners","created":"2025-05-26","cited_by_count":4,"area":null},{"id":"2509.23145","title":"TimeExpert: Boosting Long Time Series Forecasting with Temporal Mix of Experts","created":"2025-09-27","cited_by_count":4,"area":null},{"id":"2603.08707","title":"Impermanent: A Live Benchmark for Temporal Generalization in Time Series Forecasting","created":"2026-03-09","cited_by_count":4,"area":null},{"id":"2603.11950","title":"Learning Transferable Sensor Models via Language-Informed Pretraining","created":"2026-03-12","cited_by_count":4,"area":null},{"id":"2603.17439","title":"Baguan-TS: A Sequence-Native In-Context Learning Model for Time Series Forecasting with Covariates","created":"2026-03-18","cited_by_count":4,"area":null},{"id":"2604.11529","title":"TempusBench: An Evaluation Framework for Time-Series Forecasting","created":"2026-04-13","cited_by_count":4,"area":null},{"id":"2409.06282","title":"ReAugment: Model Zoo-Guided RL for Few-Shot Time Series Augmentation and Forecasting","created":"2024-09-10","cited_by_count":3,"area":null},{"id":"2410.22981","title":"DisenTS: Disentangled Channel Evolving Pattern Modeling for Multivariate Time Series Forecasting","created":"2024-10-30","cited_by_count":3,"area":null},{"id":"2410.23222","title":"Dataset-Driven Channel Masks in Transformers for Multivariate Time Series","created":"2024-10-30","cited_by_count":3,"area":null},{"id":"2502.06037","title":"Investigating Compositional Reasoning in Time Series Foundation Models","created":"2025-02-09","cited_by_count":3,"area":"lr"},{"id":"2502.19960","title":"SeisMoLLM: Advancing Seismic Monitoring via Cross-modal Transfer with Pre-trained Large Language Model","created":"2025-02-27","cited_by_count":3,"area":null},{"id":"2502.21086","title":"Are foundation models useful feature extractors for electroencephalography analysis?","created":"2025-02-28","cited_by_count":3,"area":null},{"id":"2504.08818","title":"From Tokenizer Bias to Backbone Capability: A Controlled Study of LLMs for Time Series Forecasting","created":"2025-04-09","cited_by_count":3,"area":null},{"id":"2505.00307","title":"Gateformer: Advancing Multivariate Time Series Forecasting through Temporal and Variate-Wise Attention with Gated Representations","created":"2025-05-01","cited_by_count":3,"area":null},{"id":"2505.01415","title":"How Effective are Large Time Series Models in Hydrology? A Study on Water Level Forecasting in Everglades","created":"2025-05-02","cited_by_count":3,"area":null},{"id":"2509.20942","title":"Why Attention Fails: The Degeneration of Transformers into MLPs in Time Series Forecasting","created":"2025-09-25","cited_by_count":3,"area":null},{"id":"2510.20273","title":"SynTSBench: Rethinking Temporal Pattern Learning in Deep Learning Models for Time Series","created":"2025-10-23","cited_by_count":3,"area":null},{"id":"2512.14253","title":"FLAME: Flow Enhanced Legendre Memory Models for General Time Series Forecasting","created":"2025-12-16","cited_by_count":3,"area":null},{"id":"2512.21572","title":"RefineBridge: Generative Bridge Models Improve Financial Forecasting by Foundation Models","created":"2025-12-25","cited_by_count":3,"area":null},{"id":"2602.05646","title":"Empowering Time Series Analysis with Large-Scale Multimodal Pretraining","created":"2026-02-05","cited_by_count":3,"area":null},{"id":"2603.21612","title":"Towards Multimodal Time Series Anomaly Detection with Semantic Alignment and Condensed Interaction","created":"2026-03-23","cited_by_count":3,"area":null},{"id":"2604.17295","title":"LLaTiSA: Towards Difficulty-Stratified Time Series Reasoning from Visual Perception to Semantics","created":"2026-04-19","cited_by_count":3,"area":"lr"},{"id":"2605.09081","title":"FactoryNet: A Large-Scale Dataset toward Industrial Time-Series Foundation Models","created":"2026-05-09","cited_by_count":3,"area":null},{"id":"2606.01999","title":"Why Do Time Series Models Need Long Context Windows?","created":"2026-06-01","cited_by_count":3,"area":null},{"id":"2608.13262","title":"Into the ORBIT for Time Series: Training Regimes for Foundation Models","created":"2026-08-13","cited_by_count":3,"area":null},{"id":"2609.04239","title":"EXAONE Finance 1.0: An Attention-free Time Series Foundation Model for Financial Time Series","created":"2026-08-04","cited_by_count":3,"area":null},{"id":"2503.01116","title":"Large AI Model for Delay-Doppler Domain Channel Prediction in 6G OTFS-Based Vehicular Networks","created":"2025-03-03","cited_by_count":2,"area":null},{"id":"2504.10900","title":"Bridging Distribution Gaps in Time Series Foundation Model Pretraining with Prototype-Guided Normalization","created":"2025-04-15","cited_by_count":2,"area":null},{"id":"2505.02880","title":"Beyond Fixed Patches: Enhancing GPTs for Financial Prediction with Adaptive Segmentation and Learnable Wavelets","created":"2025-05-05","cited_by_count":2,"area":null},{"id":"2505.08151","title":"Foundation Models Knowledge Distillation For Battery Capacity Degradation Forecast","created":"2025-05-13","cited_by_count":2,"area":"distill"},{"id":"2506.11528","title":"Delayformer: spatiotemporal transformation for predicting high-dimensional dynamics","created":"2025-06-13","cited_by_count":2,"area":null},{"id":"2509.12080","title":"A Time-Series Foundation Model by Universal Delay Embedding","created":"2025-09-15","cited_by_count":2,"area":null},{"id":"2509.15105","title":"Super-Linear: A Lightweight Pretrained Mixture of Linear Experts for Time Series Forecasting","created":"2025-09-18","cited_by_count":2,"area":"moe"},{"id":"2509.22279","title":"Task-Aware Mixture-of-Experts for Time Series Analysis","created":"2025-09-26","cited_by_count":2,"area":"moe"},{"id":"2509.23695","title":"Estimating Time Series Foundation Model Transferability via In-Context Learning","created":"2025-09-28","cited_by_count":2,"area":null}],"next_cursor":"100"}