Lixin Cui
20 papers · 2020–2026 · 6 conferences · across top CS/AI conferences
Achievements
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🏃 Academic Marathon (5) 🌉 Interdisciplinary Bridge 🧭 Keyword Pioneer 🌍 Conference Polyglot (5) 🐝 Cross-Pollinator (12)
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Conference Polyglot
(5)
🏃
Academic Marathon
(5)
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Dynamic Duo
(12)
🔬
Deep Specialist
(14)
🗃️
Keyword Collector
(68)
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Prolific Year
(8)
💎
Century Club
(12)
Conferences
AAAI (8)
IJCAI (6)
ICML (3)
ACL (1)
EMNLP (1)
NIPS (1)
Top co-authors
Keywords
graph neural network
(9)
graph classification
(8)
attention mechanism
(3)
contrastive learning
(3)
graph kernel
(3)
representation learning
(2)
kernel methods
(2)
graph representation learning
(2)
self-supervised hypergraph learning
(2)
graph auto-encoder
(2)
hyperedge prediction
(2)
safety alignment
(1)
hierarchical alignment
(1)
model alignment
(1)
out-of-distribution generalization
(1)
graph matching
(1)
graph representation
(1)
adaptive filtering
(1)
hierarchical clustering
(1)
dynamic time warping
(1)
Papers
Please refuse to answer me! Mitigating Over-Refusal in Large Language Models via Adaptive Contrastive Decoding
ACL 2026
HyperAim: Hypergraph Contrastive Learning with Adaptive Multi-frequency Filters
AAAI 2026
Self-Supervised Hypergraph Learning with Substructure Awareness for Hyperedge Prediction
AAAI 2026
SSHPool: The Separated Subgraph-based Hierarchical Pooling
AAAI 2026
GCIB: Causal Intervention Guided Graph Information Bottleneck Framework
AAAI 2026
LGAN: An Efficient High-Order Graph Neural Network via the Line Graph Aggregation
AAAI 2026
Multi-Granular Graph Learning with Fine-Grained Behavioral Pattern Awareness for Session-Based Recommendation
AAAI 2026
HyperNoRA: Hyperedge Prediction via Node-Level Relation-Aware Self-Supervised Hypergraph Learning
AAAI 2026
DHTAGK: Deep Hierarchical Transitive-Aligned Graph Kernels for Graph Classification
IJCAI 2025
DHAKR: Learning Deep Hierarchical Attention-Based Kernelized Representations for Graph Classification
AAAI 2025
MidPO: Dual Preference Optimization for Safety and Helpfulness in Large Language Models via a Mixture of Experts Framework
EMNLP 2025
ENAHPool: The Edge-Node Attention-based Hierarchical Pooling for Graph Neural Networks
ICML 2025
AKBR: Learning Adaptive Kernel-based Representations for Graph Classification
IJCAI 2025
Exploring the Over-smoothing Problem of Graph Neural Networks for Graph Classification: An Entropy-based Viewpoint
IJCAI 2025
HA-SCN: Learning Hierarchical Aligned Subtree Convolutional Networks for Graph Classification
IJCAI 2025
An End-to-End Simple Clustering Hierarchical Pooling Operation for Graph Learning Based on Top-K Node Selection
IJCAI 2025
HC-GAE: The Hierarchical Cluster-based Graph Auto-Encoder for Graph Representation Learning
NIPS 2024
QBMK: Quantum-based Matching Kernels for Un-attributed Graphs
ICML 2024
A Hierarchical Transitive-Aligned Graph Kernel for Un-attributed Graphs
ICML 2022
A Quantum-inspired Entropic Kernel for Multiple Financial Time Series Analysis
IJCAI 2020