output
20162026
most citedNeural Rating Regression with Abstractive Tips Generation for Recommendation

306 citations

Showing 2025 · cs.LGShow all

5 papers · 2 filters

cs.LG2025

GeoMAE: Masking Representation Learning for Spatio-Temporal Graph Forecasting with Missing Values

Songyu Ke, Chenyu Wu, Yuxuan Liang +3

The ubiquity of missing data in urban intelligence systems, attributable to adverse environmental conditions and equipment failures, poses a significant challenge to the efficacy o…

cs.LG2025

A Gravity-informed Spatiotemporal Transformer for Human Activity Intensity Prediction

Yi Wang, Zhenghong Wang, Fan Zhang +9

Human activity intensity prediction is crucial to many location-based services. Despite tremendous progress in modeling dynamics of human activity, most existing methods overlook p…

cs.LG2025★ 7 cited

Cross-Domain Diffusion with Progressive Alignment for Efficient Adaptive Retrieval

Junyu Luo, Yusheng Zhao, Xiao Luo +5

Unsupervised efficient domain adaptive retrieval aims to transfer knowledge from a labeled source domain to an unlabeled target domain, while maintaining low storage cost and high…

cs.LG2025★ 13 cited

DeepSTA: A Spatial-Temporal Attention Network for Logistics Delivery Timely Rate Prediction in Anomaly Conditions

Jinhui Yi, Huan Yan, Haotian Wang +2

Prediction of couriers' delivery timely rates in advance is essential to the logistics industry, enabling companies to take preemptive measures to ensure the normal operation of de…

cs.LG2025★ 3 cited

Learning to Estimate Package Delivery Time in Mixed Imbalanced Delivery and Pickup Logistics Services

Jinhui Yi, Huan Yan, Haotian Wang +2

Accurately estimating package delivery time is essential to the logistics industry, which enables reasonable work allocation and on-time service guarantee. This becomes even more n…