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Yuxuan Liang — most-cited papers & profile · Graph Learning
← authors
·
overview
Yuxuan Liang
24
papers ·
1230
citations ·
39
h-index
Guangdong University of Technology · Beijing University of Posts and Telecommunications · Hong Kong University of Science and Technology · Guangzhou University · University of Hong Kong · South China University of Technology
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Most-cited papers
Time-LLM: Time Series Forecasting by Reprogramming Large Language Models
2023 · 940 citations
Multi-Behavior Hypergraph-Enhanced Transformer for Sequential Recommendation
2022 · 187 citations
Time-VLM: Exploring Multimodal Vision-Language Models for Augmented Time Series Forecasting
2025 · 59 citations
Large Models for Time Series and Spatio-Temporal Data: A Survey and Outlook
2023 · 35 citations
RAST: A Retrieval Augmented Spatio-Temporal Framework for Traffic Prediction
2025 · 2 citations
Towards Reliable Time Series Forecasting under Future Uncertainty: Ambiguity and Novelty Rejection Mechanisms
2025 · 2 citations
Multi-Agent Collaborative Reasoning with Tool-Augmented Evidence for Urban Region Profiling
2026
Reinforcement Learning for Delivery Drone-Based Participatory Sensing in Dynamic Environments
2026
NeuralOGCM: Differentiable Ocean Modeling with Learnable Physics
2025
Augur: Modeling Covariate Causal Associations in Time Series via Large Language Models
2025
A Game-Theoretic Spatio-Temporal Reinforcement Learning Framework for Collaborative Public Resource Allocation
2025
Select, then Balance: Exploring Exogenous Variable Modeling of Spatio-Temporal Forecasting
2025
Pyramid Token Pruning for High-Resolution Large Vision-Language Models via Region, Token, and Instruction-Guided Importance
2025
Pyramid Token Pruning for High-Resolution Large Vision-Language Models via Region, Token, and Instruction-Guided Importance
2025
GeoMAE: Masking Representation Learning for Spatio-Temporal Graph Forecasting with Missing Values
2025
Topics
Foundation Models
Transformer Forecasters
Vision-Language Models
Video-Language
Benchmarks
Multi-Agent
Evaluation
Probabilistic
Climate & Weather
Domain — Energy/Weather