{"total":32,"rows":[{"id":"2410.04442","title":"TimeBridge: Non-Stationarity Matters for Long-term Time Series Forecasting","created":"2024-10-06","cited_by_count":40,"area":null},{"id":"2510.14510","title":"Enhancing Time Series Forecasting through Selective Representation Spaces: A Patch Perspective","created":"2025-10-16","cited_by_count":39,"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":"2502.18834","title":"FinTSB: A Comprehensive and Practical Benchmark for Financial Time Series Forecasting","created":"2025-02-26","cited_by_count":24,"area":null},{"id":"2509.14181","title":"Bridging Past and Future: Distribution-Aware Alignment for Time Series Forecasting","created":"2025-09-17","cited_by_count":20,"area":null},{"id":"2510.24574","title":"DistDF: Time-Series Forecasting Needs Joint-Distribution Wasserstein Alignment","created":"2025-10-28","cited_by_count":13,"area":null},{"id":"2504.07099","title":"Time Series Analysis in Frequency Domain: A Survey of Open Challenges, Opportunities and Benchmarks","created":"2025-02-12","cited_by_count":10,"area":null},{"id":"2510.04910","title":"Glocal Information Bottleneck for Time Series Imputation","created":"2025-10-06","cited_by_count":9,"area":null},{"id":"2505.23017","title":"$K^2$VAE: A Koopman-Kalman Enhanced Variational AutoEncoder for Probabilistic Time Series Forecasting","created":"2025-05-29","cited_by_count":8,"area":null},{"id":"2509.23313","title":"ASTGI: Adaptive Spatio-Temporal Graph Interactions for Irregular Multivariate Time Series Forecasting","created":"2025-09-27","cited_by_count":8,"area":null},{"id":"2509.23494","title":"Revisiting Multivariate Time Series Forecasting with Missing Values","created":"2025-09-27","cited_by_count":7,"area":null},{"id":"2602.00297","title":"From Observations to States: Latent Time Series Forecasting","created":"2026-01-30","cited_by_count":6,"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":"2602.00654","title":"PHAT: Modeling Period Heterogeneity for Multivariate Time Series Forecasting","created":"2026-01-31","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":"2602.04369","title":"Multi-scale hypergraph meets LLMs: Aligning large language models for time series analysis","created":"2026-02-04","cited_by_count":2,"area":null},{"id":"2603.02220","title":"Forecasting as Rendering: A 2D Gaussian Splatting Framework for Time Series Forecasting","created":"2026-02-10","cited_by_count":2,"area":null},{"id":"2603.13702","title":"Routing Channel-Patch Dependencies in Time Series Forecasting with Graph Spectral Decomposition","created":"2026-03-14","cited_by_count":2,"area":null},{"id":"2602.22270","title":"Prior Knowledge-enhanced Spatio-temporal Epidemic Forecasting","created":"2026-02-25","cited_by_count":1,"area":null},{"id":"2603.06354","title":"Frequency-Separable Hamiltonian Neural Network for Multi-Timescale Dynamics","created":"2026-03-06","cited_by_count":1,"area":null},{"id":"2603.24262","title":"Forecasting with Guidance: Representation-Level Supervision for Time Series Forecasting","created":"2026-03-25","cited_by_count":1,"area":null},{"id":"2606.13571","title":"Existence Precedes Value: Joint Modeling of Observational Existence and Evolving States in Time Series Forecasting","created":"2026-06-11","cited_by_count":1,"area":null},{"id":"2601.16632","title":"Dual-Prototype Disentanglement: A Context-Aware Enhancement Framework for Time Series Forecasting","created":"2026-01-23","cited_by_count":0,"area":null},{"id":"2601.18829","title":"CP Loss: Channel-wise Perceptual Loss for Time Series Forecasting","created":"2026-01-25","cited_by_count":0,"area":null},{"id":"2605.10292","title":"LeapTS: Rethinking Time Series Forecasting as Adaptive Multi-Horizon Scheduling","created":"2026-05-11","cited_by_count":0,"area":null},{"id":"2605.21550","title":"PeakFocus: Bridging Peak Localization and Intensity Regression via a Unified Multi-Scale Framework for Electricity Load Forecasting","created":"2026-05-20","cited_by_count":0,"area":null},{"id":"2605.31129","title":"Generalizing Multi-Scale Time-Series Modeling with a Single Operator","created":"2026-05-29","cited_by_count":0,"area":null},{"id":"2606.01306","title":"FAiT: Frequency-Aware Inverted Transformer for Multivariate Time Series Forecasting","created":"2026-05-31","cited_by_count":0,"area":null},{"id":"2608.09775","title":"AirFlow: Context Preserving and Multi-Rate State Modeling for Air Quality Forecasting","created":"2026-08-10","cited_by_count":0,"area":null},{"id":"2608.14682","title":"RouteTS: Frequency-Time Routing for Time Series Forecasting","created":"2026-08-05","cited_by_count":0,"area":null},{"id":"2609.08286","title":"HypLTSF: A Hyperbolic Geometric View of Multi-Scale Hierarchies for Long-Term Time Series Forecasting","created":"2026-09-08","cited_by_count":0,"area":null},{"id":"2609.31038","title":"Aurora-X: Built for Extreme Time Series Forecasting","created":"2026-09-25","cited_by_count":0,"area":null}],"next_cursor":null}