Yuxuan Liang
56 papers · 2016–2026 · 11 venues · across top CS/AI venues
Authors are matched by name, so researchers who share a name ("Yang Liu", "Wei Wang") appear as a single profile and their paper counts, venues and achievements are combined. How identity is handled.
Achievements
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πΊοΈ Taxonomy Completionist (82) π Conference Polyglot Β· Gold π Academic Marathon Β· Half π Interdisciplinary Bridge Β· Silver π£ Hot Topic Early Bird
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Grand Slam
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Keyword Champion
(2)
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Dynamic Duo
(12)
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Triple Crown
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Deep Specialist
(16)
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Prolific Year Β· Prolific
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Unstoppable Β· Bronze
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The Questioner
(2)
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Century Club Β· Silver
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Renaissance Researcher
(8)
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Keyword Collector
(262)
Venues
Top co-authors
Research topics
Machine Learning
(43)
Deep Learning
(33)
Artificial Intelligence
(26)
Architectures
(26)
Core AI
(25)
Core Methods
(21)
Learning Types Β· Machine Learning
(17)
Application Areas
(16)
Data Science & Analytics
(14)
Learning Types Β· Deep Learning
(13)
Methods
(9)
Optimization & Theory
(9)
Natural Language Processing
(5)
Applications Β· Data Science & Analytics
(5)
Applications Β· Natural Language Processing
(4)
Keywords
graph neural network
(14)
time series forecasting
(12)
causal inference
(6)
large language model
(5)
deep learning
(4)
representation learning
(4)
zero-shot learning
(3)
relation extraction
(3)
spatio-temporal prediction
(3)
contrastive learning
(3)
recurrent neural network
(3)
spatiotemporal forecasting
(3)
backdoor adjustment
(3)
time series
(2)
message passing
(2)
spatio-temporal modeling
(2)
model compression
(2)
neural network architecture
(2)
federated learning
(2)
lottery ticket hypothesis
(2)
Papers
A Retrieval Augmented Spatio-Temporal Framework for Traffic Prediction
AAAI 2026
Augur: Modeling Covariate Causal Associations in Time Series via Large Language Models
ACL 2026
Envision, Attend, Then Respond: Counterfactual Hallucination Mitigation in Large Vision-Language Models
CVPR 2026
OccamVTS: Distilling Vision Models to 1% Parameters for Time Series Forecasting
AAAI 2026
Revitalizing Canonical Pre-Alignment for Irregular Multivariate Time Series Forecasting
AAAI 2026
Traffic-R1: Reinforced LLMs Bring Human-Like Reasoning to Traffic Signal Control Systems
ACL 2026
Air Quality Prediction with Physics-Guided Dual Neural ODEs in Open Systems
ICLR 2025
AirRadar: Inferring Nationwide Air Quality in China with Deep Neural Networks
AAAI 2025
Deep Learning for Multivariate Time Series Imputation: A Survey
IJCAI 2025
Expand and Compress: Exploring Tuning Principles for Continual Spatio-Temporal Graph Forecasting
ICLR 2025
GraphAgent: Agentic Graph Language Assistant
EMNLP 2025
Moirai-MoE: Empowering Time Series Foundation Models with Sparse Mixture of Experts
ICML 2025
Open-CK: A Large Multi-Physics Fields Coupling benchmarks in Combustion Kinetics
ICLR 2025
Personalized Federated Learning for Spatio-Temporal Forecasting: A Dual Semantic Alignment-Based Contrastive Approach
AAAI 2025
Reinforcement Learning for Hybrid Charging Stations Planning and Operation Considering Fixed and Mobile Chargers
IJCAI 2025
Through the Dual-Prism: A Spectral Perspective on Graph Data Augmentation for Graph Classifications
AAAI 2025
Time-VLM: Exploring Multimodal Vision-Language Models for Augmented Time Series Forecasting
ICML 2025
Towards Neural Scaling Laws for Time Series Foundation Models
ICLR 2025
Towards Scalable and Deep Graph Neural Networks via Noise Masking
AAAI 2025
UniTR: A Unified Framework for Joint Representation Learning of Trajectories and Road Networks
AAAI 2025
Unlocking the Power of LSTM for Long Term Time Series Forecasting
AAAI 2025
UrbanVLP: Multi-Granularity Vision-Language Pretraining for Urban Socioeconomic Indicator Prediction
AAAI 2025
Attractor Memory for Long-Term Time Series Forecasting: A Chaos Perspective
NeurIPS 2024
Earthfarsser: Versatile Spatio-Temporal Dynamical Systems Modeling in One Model
AAAI 2024
GDeR: Safeguarding Efficiency, Balancing, and Robustness via Prototypical Graph Pruning
NeurIPS 2024
Graph Lottery Ticket Automated
ICLR 2024
Improving Generalization of Dynamic Graph Learning via Environment Prompt
NeurIPS 2024
MSGNet: Learning Multi-Scale Inter-series Correlations for Multivariate Time Series Forecasting
AAAI 2024
Navigating Complexity: Toward Lossless Graph Condensation via Expanding Window Matching
ICML 2024
NuwaDynamics: Discovering and Updating in Causal Spatio-Temporal Modeling
ICLR 2024
Position: What Can Large Language Models Tell Us about Time Series Analysis
ICML 2024
Predicting Carpark Availability in Singapore with Cross-Domain Data: A New Dataset and A Data-Driven Approach
IJCAI 2024
SENCR: A Span Enhanced Two-Stage Network with Counterfactual Rethinking for Chinese NER
AAAI 2024
Spatio-Temporal Field Neural Networks for Air Quality Inference
IJCAI 2024
Terra: A Multimodal Spatio-Temporal Dataset Spanning the Earth
NeurIPS 2024
Time-FFM: Towards LM-Empowered Federated Foundation Model for Time Series Forecasting
NeurIPS 2024
Time-LLM: Time Series Forecasting by Reprogramming Large Language Models
ICLR 2024
Towards Robust Trajectory Representations: Isolating Environmental Confounders with Causal Learning
IJCAI 2024
Two Heads Are Better Than One: Boosting Graph Sparse Training via Semantic and Topological Awareness
ICML 2024
AirFormer: Predicting Nationwide Air Quality in China with Transformers
AAAI 2023
Deciphering Spatio-Temporal Graph Forecasting: A Causal Lens and Treatment
NeurIPS 2023
How Fragile is Relation Extraction under Entity Replacements?
CoNLL 2023
LargeST: A Benchmark Dataset for Large-Scale Traffic Forecasting
NeurIPS 2023
Primacy Effect of ChatGPT
EMNLP 2023
Searching Lottery Tickets in Graph Neural Networks: A Dual Perspective
ICLR 2023
DualFormer: Local-Global Stratified Transformer for Efficient Video Recognition
ECCV 2022
GraphCache: Message Passing as Caching for Sentence-Level Relation Extraction
NAACL 2022
Should We Rely on Entity Mentions for Relation Extraction? Debiasing Relation Extraction with Counterfactual Analysis
NAACL 2022
Adaptive Data Augmentation on Temporal Graphs
NeurIPS 2021
Directed Graph Contrastive Learning
NeurIPS 2021
Modeling Trajectories with Neural Ordinary Differential Equations
IJCAI 2021
Digraph Inception Convolutional Networks
NeurIPS 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