{"total":31,"rows":[{"id":"2502.01563","title":"Massive Values in Self-Attention Modules are the Key to Contextual Knowledge Understanding","created":"2025-02-03","cited_by_count":47,"area":null},{"id":"2410.05440","title":"Can LLMs Understand Time Series Anomalies?","created":"2024-10-07","cited_by_count":41,"area":null},{"id":"2406.12199","title":"Time Series Modeling for Heart Rate Prediction: From ARIMA to Transformers","created":"2024-06-18","cited_by_count":35,"area":null},{"id":"2505.13192","title":"True Zero-Shot Inference of Dynamical Systems Preserving Long-Term Statistics","created":"2025-05-19","cited_by_count":20,"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":"2506.00457","title":"Revisiting LLMs as Zero-Shot Time-Series Forecasters: Small Noise Can Break Large Models","created":"2025-05-31","cited_by_count":7,"area":null},{"id":"2507.21830","title":"DualSG: A Dual-Stream Explicit Semantic-Guided Multivariate Time Series Forecasting Framework","created":"2025-07-29","cited_by_count":7,"area":null},{"id":"2411.08404","title":"Quantifying Qualitative Insights: Leveraging LLMs to Market Predict","created":"2024-11-13","cited_by_count":3,"area":null},{"id":"2506.11040","title":"Large Language models for Time Series Analysis: Techniques, Applications, and Challenges","created":"2025-05-21","cited_by_count":3,"area":null},{"id":"2405.06719","title":"Enhancing Traffic Prediction with Textual Data Using Large Language Models","created":"2024-05-10","cited_by_count":2,"area":null},{"id":"2501.07276","title":"Bridging Smart Meter Gaps: A Benchmark of Statistical, Machine Learning and Time Series Foundation Models for Data Imputation","created":"2025-01-13","cited_by_count":2,"area":null},{"id":"2502.05701","title":"TOKON: TOKenization-Optimized Normalization for time series analysis with a large language model","created":"2025-02-08","cited_by_count":2,"area":null},{"id":"2504.02009","title":"Urban Computing in the Era of Large Language Models","created":"2025-04-02","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":"2507.23163","title":"Argumentatively Coherent Judgmental Forecasting","created":"2025-07-30","cited_by_count":2,"area":null},{"id":"2602.01736","title":"Position: The Inevitable End of One-Architecture-Fits-All-Domains in Time Series Forecasting","created":"2026-02-02","cited_by_count":2,"area":null},{"id":"2410.19025","title":"Large Language Models for Financial Aid in Financial Time-series Forecasting","created":"2024-10-24","cited_by_count":1,"area":null},{"id":"2502.16896","title":"Zero-shot Load Forecasting for Integrated Energy Systems: A Large Language Model-based Framework with Multi-task Learning","created":"2025-02-24","cited_by_count":1,"area":null},{"id":"2507.15267","title":"GREAT: Guiding Query Generation with a Trie for Recommending Related Search about Video at Kuaishou","created":"2025-07-21","cited_by_count":1,"area":null},{"id":"2601.04709","title":"Bridging Temporal and Textual Modalities: A Multimodal Framework for Automated Cloud Failure Root Cause Analysis","created":"2026-01-08","cited_by_count":1,"area":null},{"id":"2602.07695","title":"EventCast: Hybrid Demand Forecasting in E-Commerce with LLM-Based Event Knowledge","created":"2026-02-07","cited_by_count":1,"area":null},{"id":"2412.12226","title":"Apollo-Forecast: Overcoming Aliasing and Inference Speed Challenges in Language Models for Time Series Forecasting","created":"2024-12-16","cited_by_count":0,"area":null},{"id":"2502.20938","title":"A Deep User Interface for Exploring LLaMa","created":"2025-02-28","cited_by_count":0,"area":null},{"id":"2505.10213","title":"Informed Forecasting: Leveraging Auxiliary Knowledge to Boost LLM Performance on Time Series Forecasting","created":"2025-05-15","cited_by_count":0,"area":null},{"id":"2506.11512","title":"From Time Series Analysis to Question Answering: A Survey in the LLM Era","created":"2025-06-13","cited_by_count":0,"area":null},{"id":"2506.13036","title":"Forecast-Then-Optimize Deep Learning Methods","created":"2025-06-16","cited_by_count":0,"area":null},{"id":"2508.18284","title":"Multi-Modal Drift Forecasting of Leeway Objects via Navier-Stokes-Guided CNN and Sequence-to-Sequence Attention-Based Models","created":"2025-08-16","cited_by_count":0,"area":null},{"id":"2512.07992","title":"Bridging the Clinical Expertise Gap: Development of a Web-Based Platform for Accessible Time Series Forecasting and Analysis","created":"2025-12-08","cited_by_count":0,"area":null},{"id":"2604.23949","title":"Context-Aware Hospitalization Forecasting Evaluations for Decision Support using LLMs","created":"2026-04-27","cited_by_count":0,"area":null},{"id":"2606.15288","title":"Hybrid NARX-LLM for Greenland Iceberg Discharge: Prompt-Driven Residual Correction","created":"2026-06-13","cited_by_count":0,"area":null},{"id":"2609.33279","title":"Domain Generalization under Sampling Pattern Shifts in Irregular Time Series","created":"2026-09-27","cited_by_count":0,"area":null}],"next_cursor":null}