Dongsheng Luo
18 papers · 2019–2026 · 7 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 (30) π Conference Polyglot Β· Silver π Academic Marathon Β· Sprint π Interdisciplinary Bridge Β· Silver π£ Hot Topic Early Bird
π
Grand Slam
π§¬
Topic Evolution
π
Keyword Champion
(2)
π
Triple Crown
ποΈ
Keyword Collector
(70)
π
Century Club Β· Bronze
β‘
Prolific Year Β· Productive
Top co-authors
Research topics
Deep Learning
(13)
Artificial Intelligence
(12)
Machine Learning
(12)
Core AI
(12)
Architectures
(9)
Core Methods
(7)
Learning Types Β· Machine Learning
(7)
Application Areas
(5)
Learning Types Β· Deep Learning
(5)
Data Science & Analytics
(4)
Methods
(3)
Healthcare & Medicine
(2)
Clinical
(2)
Natural Language Processing
(1)
Applications
(1)
Keywords
graph neural network
(8)
large language model
(4)
contrastive learning
(4)
time series
(4)
data augmentation
(3)
representation learning
(3)
information bottleneck
(3)
model interpretability
(3)
graph information bottleneck
(2)
graph representation learning
(2)
distribution shift
(2)
information theory
(2)
self-supervised learning
(2)
subgraph extraction
(2)
node classification
(2)
explainable ai
(1)
multimodal learning
(1)
causal discovery
(1)
attention mechanism
(1)
label prediction
(1)
Papers
Explanation-Preserving Augmentation for Semi-Supervised Graph Representation Learning
AAAI 2026
SMARTTalk: Teaching SMART Logs to Talk to LLMs
OSDI 2026
Exploring Multi-Modal Data with Tool-Augmented LLM Agents for Precise Causal Discovery
ACL 2025
F-Fidelity: A Robust Framework for Faithfulness Evaluation of Explainable AI
ICLR 2025
Harnessing Vision Models for Time Series Analysis: A Survey
IJCAI 2025
MedPlan: A Two-Stage RAG-Based System for Personalized Medical Plan Generation
ACL 2025
NeuroTree: Hierarchical Functional Brain Pathway Decoding for Mental Health Disorders
ICML 2025
Explaining Time Series via Contrastive and Locally Sparse Perturbations
ICLR 2024
Factorized Explainer for Graph Neural Networks
AAAI 2024
Generating In-Distribution Proxy Graphs for Explaining Graph Neural Networks
ICML 2024
Parametric Augmentation for Time Series Contrastive Learning
ICLR 2024
RegExplainer: Generating Explanations for Graph Neural Networks in Regression Tasks
NeurIPS 2024
TimeX++: Learning Time-Series Explanations with Information Bottleneck
ICML 2024
Towards Robust Fidelity for Evaluating Explainability of Graph Neural Networks
ICLR 2024
Time Series Contrastive Learning with Information-Aware Augmentations
AAAI 2023
InfoGCL: Information-Aware Graph Contrastive Learning
NeurIPS 2021
Parameterized Explainer for Graph Neural Network
NeurIPS 2020
Spatio-Temporal Attentive RNN for Node Classification in Temporal Attributed Graphs
IJCAI 2019