{"total":22,"rows":[{"id":"2510.23672","title":"DBLoss: Decomposition-based Loss Function for Time Series Forecasting","created":"2025-10-27","cited_by_count":45,"area":null},{"id":"2503.23512","title":"SCORE: Story Coherence and Retrieval Enhancement for AI Narratives","created":"2025-03-30","cited_by_count":42,"area":null},{"id":"2507.05631","title":"OFFSET: Segmentation-based Focus Shift Revision for Composed Image Retrieval","created":"2025-07-08","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":"2505.17847","title":"Time-o1: Time-Series Forecasting Needs Transformed Label Alignment","created":"2025-05-23","cited_by_count":22,"area":null},{"id":"2501.15167","title":"Enhancing Intent Understanding for Ambiguous prompt: A Human-Machine Co-Adaption Strategy","created":"2025-01-25","cited_by_count":16,"area":null},{"id":"2602.00582","title":"Bridging Time and Frequency: A Joint Modeling Framework for Irregular Multivariate Time Series Forecasting","created":"2026-01-31","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":"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":"2504.09993","title":"AimTS: Augmented Series and Image Contrastive Learning for Time Series Classification","created":"2025-04-14","cited_by_count":6,"area":null},{"id":"2501.15389","title":"CP2M: Clustered-Patch-Mixed Mosaic Augmentation for Aerial Image Segmentation","created":"2025-01-26","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":"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":"2504.15085","title":"Cognitive-Inspired Hierarchical Attention Fusion With Visual and Textual for Cross-Domain Sequential Recommendation","created":"2025-04-21","cited_by_count":2,"area":null},{"id":"2503.17669","title":"TDRI: Two-Phase Dialogue Refinement and Co-Adaptation for Interactive Image Generation","created":"2025-03-22","cited_by_count":1,"area":null},{"id":"2509.23668","title":"Hermes: A Multi-Scale Spatial-Temporal Hypergraph Network for Stock Time Series Forecasting","created":"2025-09-28","cited_by_count":1,"area":null},{"id":"2605.08289","title":"What If We Let Forecasting Forget? A Sparse Bottleneck for Cross-Variable Dependencies","created":"2026-05-08","cited_by_count":1,"area":null},{"id":"2504.14178","title":"Segregation and Context Aggregation Network for Real-time Cloud Segmentation","created":"2025-04-19","cited_by_count":0,"area":null},{"id":"2607.16230","title":"RouteCost: A Production-Inspired Multi-Stage Framework for Pre-Order Shipping Cost Estimation in E-Commerce","created":"2026-06-24","cited_by_count":0,"area":null},{"id":"2609.20156","title":"QUALS: Corpus Equilibrium for Universal Forecasting via Pattern Quantization and Learnability Synchronization","created":"2026-09-17","cited_by_count":0,"area":null}],"next_cursor":null}