Yuxuan Liang

54 papers · 2016–2026 · 9 conferences · across top CS/AI conferences

Achievements

🐣 Hot Topic Early Bird 🌉 Interdisciplinary Bridge 🗺️ Taxonomy Completionist (10) 🧭 Keyword Pioneer 🌍 Conference Polyglot (9) 🏃 Academic Marathon (9) 🐝 Cross-Pollinator (14) 🌈 Renaissance Researcher (10) 🏆 Keyword Champion (2) 🔬 Deep Specialist (12) 👑 Triple Crown 🤝 Dynamic Duo (11) 🏆 Grand Slam 💎 Century Club (51) ❓ The Questioner (3) ⚡ Prolific Year (7) 🔥 Unstoppable (8) 🗃️ Keyword Collector (206)

Conferences

AAAI (15) NIPS (10) IJCAI (9) ICLR (8) ICML (5) EMNLP (3) NAACL (2) CONLL (1) ECCV (1)

Top co-authors

Qingsong Wen (12) Kun Wang (11) Roger Zimmermann (9) Yiwei Wang (9) Yutong Xia (7) Bryan Hooi (7) Yujun Cai (6) Siru Zhong (6) Yu Zheng (6) Wei Chen (6)

Keywords

graph neural network (11) time series forecasting (9) deep learning (4) relation extraction (4) causal inference (4) representation learning (4) contrastive learning (3) recurrent neural network (3) graph convolution (2) directed graph (2) spatio-temporal forecasting (2) zero-shot learning (2) self-attention mechanism (2) node classification (2) time series (2) federated learning (2) spatio-temporal modeling (2) neural network architecture (2) data augmentation (2) message passing (2)

Papers

OccamVTS: Distilling Vision Models to 1% Parameters for Time Series Forecasting AAAI 2026

A Retrieval Augmented Spatio-Temporal Framework for Traffic Prediction AAAI 2026

Revitalizing Canonical Pre-Alignment for Irregular Multivariate Time Series Forecasting AAAI 2026

Reinforcement Learning for Hybrid Charging Stations Planning and Operation Considering Fixed and Mobile Chargers IJCAI 2025

Unlocking the Power of LSTM for Long Term Time Series Forecasting AAAI 2025

Personalized Federated Learning for Spatio-Temporal Forecasting: A Dual Semantic Alignment-Based Contrastive Approach AAAI 2025

UniTR: A Unified Framework for Joint Representation Learning of Trajectories and Road Networks AAAI 2025

Towards Scalable and Deep Graph Neural Networks via Noise Masking AAAI 2025

Through the Dual-Prism: A Spectral Perspective on Graph Data Augmentation for Graph Classifications AAAI 2025

UrbanVLP: Multi-Granularity Vision-Language Pretraining for Urban Socioeconomic Indicator Prediction AAAI 2025

AirRadar: Inferring Nationwide Air Quality in China with Deep Neural Networks AAAI 2025

GraphAgent: Agentic Graph Language Assistant EMNLP 2025

Towards Neural Scaling Laws for Time Series Foundation Models ICLR 2025

Air Quality Prediction with Physics-Guided Dual Neural ODEs in Open Systems ICLR 2025

Open-CK: A Large Multi-Physics Fields Coupling benchmarks in Combustion Kinetics ICLR 2025

Expand and Compress: Exploring Tuning Principles for Continual Spatio-Temporal Graph Forecasting ICLR 2025

Moirai-MoE: Empowering Time Series Foundation Models with Sparse Mixture of Experts ICML 2025

Time-VLM: Exploring Multimodal Vision-Language Models for Augmented Time Series Forecasting ICML 2025

Deep Learning for Multivariate Time Series Imputation: A Survey IJCAI 2025

Earthfarsser: Versatile Spatio-Temporal Dynamical Systems Modeling in One Model AAAI 2024

MSGNet: Learning Multi-Scale Inter-series Correlations for Multivariate Time Series Forecasting AAAI 2024

Spatio-Temporal Field Neural Networks for Air Quality Inference IJCAI 2024

SENCR: A Span Enhanced Two-Stage Network with Counterfactual Rethinking for Chinese NER AAAI 2024

Towards Robust Trajectory Representations: Isolating Environmental Confounders with Causal Learning IJCAI 2024

Position: What Can Large Language Models Tell Us about Time Series Analysis ICML 2024

Two Heads Are Better Than One: Boosting Graph Sparse Training via Semantic and Topological Awareness ICML 2024

Navigating Complexity: Toward Lossless Graph Condensation via Expanding Window Matching ICML 2024

Attractor Memory for Long-Term Time Series Forecasting: A Chaos Perspective NIPS 2024

GDeR: Safeguarding Efficiency, Balancing, and Robustness via Prototypical Graph Pruning NIPS 2024

Terra: A Multimodal Spatio-Temporal Dataset Spanning the Earth NIPS 2024

Improving Generalization of Dynamic Graph Learning via Environment Prompt NIPS 2024

Time-FFM: Towards LM-Empowered Federated Foundation Model for Time Series Forecasting NIPS 2024

Predicting Carpark Availability in Singapore with Cross-Domain Data: A New Dataset and A Data-Driven Approach IJCAI 2024

Time-LLM: Time Series Forecasting by Reprogramming Large Language Models ICLR 2024

NuwaDynamics: Discovering and Updating in Causal Spatio-Temporal Modeling ICLR 2024

Graph Lottery Ticket Automated ICLR 2024

LargeST: A Benchmark Dataset for Large-Scale Traffic Forecasting NIPS 2023

Searching Lottery Tickets in Graph Neural Networks: A Dual Perspective ICLR 2023

Deciphering Spatio-Temporal Graph Forecasting: A Causal Lens and Treatment NIPS 2023

How Fragile is Relation Extraction under Entity Replacements? CONLL 2023

Primacy Effect of ChatGPT EMNLP 2023

How Fragile is Relation Extraction under Entity Replacements? EMNLP 2023

AirFormer: Predicting Nationwide Air Quality in China with Transformers AAAI 2023

DualFormer: Local-Global Stratified Transformer for Efficient Video Recognition ECCV 2022

Should We Rely on Entity Mentions for Relation Extraction? Debiasing Relation Extraction with Counterfactual Analysis NAACL 2022

GraphCache: Message Passing as Caching for Sentence-Level Relation Extraction NAACL 2022

Modeling Trajectories with Neural Ordinary Differential Equations IJCAI 2021

Adaptive Data Augmentation on Temporal Graphs NIPS 2021

Directed Graph Contrastive Learning NIPS 2021

Digraph Inception Convolutional Networks NIPS 2020

Learning to Generate Maps from Trajectories AAAI 2020

Learning Multi-Objective Rewards and User Utility Function in Contextual Bandits for Personalized Ranking IJCAI 2019

GeoMAN: Multi-level Attention Networks for Geo-sensory Time Series Prediction IJCAI 2018

Urban Water Quality Prediction Based on Multi-Task Multi-View Learning IJCAI 2016