Hengshu Zhu
29 papers · 2015–2026 · 6 conferences · across top CS/AI conferences
Achievements
Jump to papers ↓+9 more ↓ Show less ↑
π Academic Marathon (10) π Conference Polyglot (6) π Interdisciplinary Bridge π§ Keyword Pioneer π Cross-Pollinator (12)
π
Renaissance Researcher
(9)
πΊοΈ
Taxonomy Completionist
(66)
π
Interdisciplinary Bridge
π€
Dynamic Duo
(12)
β‘
Prolific Year
(10)
π
Conference Pioneer
ποΈ
Keyword Collector
(137)
π₯
Unstoppable
(6)
π
Century Club
(27)
Conferences
AAAI (9)
IJCAI (9)
NIPS (5)
ACL (3)
ICML (2)
EMNLP (1)
Top co-authors
Research topics
Keywords
graph neural network
(5)
large language model
(5)
recommender system
(4)
attention mechanism
(4)
neural network
(3)
cognitive diagnosis
(2)
representation learning
(2)
skill demand
(2)
matrix factorization
(2)
knowledge distillation
(2)
contrastive learning
(2)
skill demand forecasting
(2)
generalized category discovery
(2)
job recommendation
(2)
collaborative filtering
(2)
gradient-based optimization
(1)
feature selection
(1)
transfer learning
(1)
hierarchical learning
(1)
latent dirichlet allocation
(1)
Papers
GenDis: Generative-Discriminative Dual-View Co-Training for Generalized Category Discovery
ACL 2026
TLSA: LLM-Guided Text-Label Space Alignment with Contrastive Learning for Generalized Category Discovery
ACL 2026
KG-Agent: An Efficient Autonomous Agent Framework for Complex Reasoning over Knowledge Graph
ACL 2025
Towards Lifelong Model Editing via Simulating Ideal Editor
ICML 2025
Unifying Knowledge from Diverse Datasets to Enhance Spatial-Temporal Modeling: A Granularity-Adaptive Geographical Embedding Approach
ICML 2025
Mixture of In-Context Experts Enhance LLMs' Long Context Awareness
NIPS 2024
Make Large Language Model a Better Ranker
EMNLP 2024
Pre-DyGAE: Pre-training Enhanced Dynamic Graph Autoencoder for Occupational Skill Demand Forecasting
IJCAI 2024
DGCD: An Adaptive Denoising GNN for Group-level Cognitive Diagnosis
IJCAI 2024
Job-SDF: A Multi-Granularity Dataset for Job Skill Demand Forecasting and Benchmarking
NIPS 2024
Enhancing Job Recommendation through LLM-Based Generative Adversarial Networks
AAAI 2024
Enhancing Cognitive Diagnosis Using Un-interacted Exercises: A Collaboration-Aware Mixed Sampling Approach
AAAI 2024
Exploring Large Language Model for Graph Data Understanding in Online Job Recommendations
AAAI 2024
A Cross-View Hierarchical Graph Learning Hypernetwork for Skill Demand-Supply Joint Prediction
AAAI 2024
OT4P: Unlocking Effective Orthogonal Group Path for Permutation Relaxation
NIPS 2024
Reconciling Cognitive Modeling with Knowledge Forgetting: A Continuous Time-aware Neural Network Approach
IJCAI 2022
Feature and Instance Joint Selection: A Reinforcement Learning Perspective
IJCAI 2022
Discerning Decision-Making Process of Deep Neural Networks with Hierarchical Voting Transformation
NIPS 2021
Joint Air Quality and Weather Prediction Based on Multi-Adversarial Spatiotemporal Networks
AAAI 2021
Topic Modeling Revisited: A Document Graph-based Neural Network Perspective
NIPS 2021
Regularizing Variational Autoencoder with Diversity and Uncertainty Awareness
IJCAI 2021
Relational Graph Neural Network with Hierarchical Attention for Knowledge Graph Completion
AAAI 2020
SetRank: A Setwise Bayesian Approach for Collaborative Ranking from Implicit Feedback
AAAI 2020
Exploiting the Contagious Effect for Employee Turnover Prediction
AAAI 2019
Trend-Aware Tensor Factorization for Job Skill Demand Analysis
IJCAI 2019
Interactive Attention Transfer Network for Cross-Domain Sentiment Classification
AAAI 2019
A Joint Learning Approach to Intelligent Job Interview Assessment
IJCAI 2018
Incremental Matrix Factorization: A Linear Feature Transformation Perspective
IJCAI 2017
Matrix Factorization with Scale-Invariant Parameters
IJCAI 2015