Danai Koutra
20 papers · 2020–2026 · 8 conferences · across top CS/AI conferences
Achievements
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π Academic Marathon (5) π Interdisciplinary Bridge π§ Keyword Pioneer π Conference Polyglot (8) π Cross-Pollinator (14)
π
Cross-Pollinator
(14)
π
Renaissance Researcher
(5)
πΊοΈ
Taxonomy Completionist
(31)
π
Grand Slam
π
Keyword Champion
(2)
π
Triple Crown
ποΈ
Keyword Collector
(67)
π
Century Club
(19)
π₯
Unstoppable
(6)
β‘
Prolific Year
(5)
Conferences
EMNLP (5)
NIPS (4)
AAAI (3)
ICLR (3)
AISTATS (2)
CVPR (1)
ICML (1)
NAACL (1)
Top co-authors
Keywords
graph neural network
(6)
link prediction
(3)
node classification
(3)
representation learning
(2)
contextual language model
(2)
graph representation
(2)
knowledge graph
(2)
large language model
(2)
node embedding
(2)
domain generalization
(1)
data augmentation
(1)
knowledge distillation
(1)
knowledge representation
(1)
code generation
(1)
semi-supervised learning
(1)
contrastive learning
(1)
graph representation learning
(1)
knowledge base
(1)
attention mechanism
(1)
theoretical analysis
(1)
Papers
GraphTextack: A Realistic Black-Box Node Injection Attack on LLM-Enhanced GNNs
AAAI 2026
Demystifying the Power of Large Language Models in Graph Generation
NAACL 2025
A Large-scale Training Paradigm for Graph Generative Models
ICLR 2025
Learning Laplacian Positional Encodings for Heterophilous Graphs
AISTATS 2025
Understanding GNNs and Homophily in Dynamic Node Classification
AISTATS 2025
Mosaic of Modalities: A Comprehensive Benchmark for Multimodal Graph Learning
CVPR 2025
On the Impact of Feature Heterophily on Link Prediction with Graph Neural Networks
NIPS 2024
Editing Partially Observable Networks via Graph Diffusion Models
ICML 2024
Accurate and Scalable Estimation of Epistemic Uncertainty for Graph Neural Networks
ICLR 2024
Multi-Stage Balanced Distillation: Addressing Long-Tail Challenges in Sequence-Level Knowledge Distillation
EMNLP 2024
A Provable Framework of Learning Graph Embeddings via Summarization
AAAI 2023
A Closer Look at Model Adaptation using Feature Distortion and Simplicity Bias
ICLR 2023
Analyzing Data-Centric Properties for Graph Contrastive Learning
NIPS 2022
NegatER: Unsupervised Discovery of Negatives in Commonsense Knowledge Bases
EMNLP 2021
Relational World Knowledge Representation in Contextual Language Models: A Review
EMNLP 2021
Graph Neural Networks with Heterophily
AAAI 2021
CoDEx: A Comprehensive Knowledge Graph Completion Benchmark
EMNLP 2020
Neural Execution Engines: Learning to Execute Subroutines
NIPS 2020
Evaluating the Calibration of Knowledge Graph Embeddings for Trustworthy Link Prediction
EMNLP 2020
Beyond Homophily in Graph Neural Networks: Current Limitations and Effective Designs
NIPS 2020