activity
20242026
most citedST-MoE-BERT: A Spatial-Temporal Mixture-of-Experts Framework for Long-Term Cross-City Mobility Prediction

6 citations · 6 across the 3 of their papers we have counts for

collaborators

5 papers

cs.CV2026

Structural Graph Probing of Vision-Language Models

Haoyu He, Yue Zhuo, Yu Zheng +1

Vision-language models (VLMs) achieve strong multimodal performance, yet how computation is organized across populations of neurons remains poorly understood. In this work, we stud…

cs.LG2025

RHYTHM: Reasoning with Hierarchical Temporal Tokenization for Human Mobility

Haoyu He, Haozheng Luo, Yan Chen +1

Predicting human mobility is inherently challenging due to complex long-range dependencies and multi-scale periodic behaviors. To address this, we introduce RHYTHM (Reasoning with…

cs.CL2025

Efficient Temporal Tokenization for Mobility Prediction with Large Language Models

Haoyu He, Haozheng Luo, Yan Chen +1

We introduce RHYTHM (Reasoning with Hierarchical Temporal Tokenization for Human Mobility), a framework that leverages large language models (LLMs) as spatio-temporal predictors an…

cs.LG2024★ 6 cited

ST-MoE-BERT: A Spatial-Temporal Mixture-of-Experts Framework for Long-Term Cross-City Mobility Prediction

Haoyu He, Haozheng Luo, Qi R. Wang

Predicting human mobility across multiple cities presents significant challenges due to the complex and diverse spatial-temporal dynamics inherent in different urban environments.…

cs.LG2024

Pretrained Mobility Transformer: A Foundation Model for Human Mobility

Xinhua Wu, Haoyu He, Yanchao Wang +1

Ubiquitous mobile devices are generating vast amounts of location-based service data that reveal how individuals navigate and utilize urban spaces in detail. In this study, we util…