Aidong Zhang
39 papers · 2017–2026 · 9 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 (79) π Academic Marathon Β· Sprint π Conference Polyglot Β· Silver π Interdisciplinary Bridge Β· Gold π£ Hot Topic Early Bird
π€
Dynamic Duo
(10)
ποΈ
Keyword Collector
(187)
β‘
Prolific Year Β· Prolific
π₯
Unstoppable Β· Silver
β
The Questioner
π
Century Club Β· Bronze
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Conference Pioneer
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Renaissance Researcher
(8)
Top co-authors
Research topics
Machine Learning
(31)
Artificial Intelligence
(22)
Core AI
(19)
Learning Types Β· Machine Learning
(17)
Deep Learning
(16)
Application Areas
(10)
Core Methods
(10)
Learning Types Β· Deep Learning
(8)
Optimization & Theory
(7)
Healthcare & Medicine
(5)
Natural Language Processing
(5)
Clinical
(5)
Computer Vision
(4)
Learning Paradigms
(4)
Models
(4)
Keywords
large language model
(6)
federated learning
(5)
causal inference
(4)
benchmark evaluation
(4)
vision-language model
(4)
contrastive learning
(3)
generative adversarial network
(3)
multi-agent system
(3)
spurious bia
(3)
adversarial learning
(3)
multimodal learning
(3)
differential privacy
(2)
treatment effect estimation
(2)
spurious correlation
(2)
foundation model
(2)
domain generalization
(2)
representation learning
(2)
attention mechanism
(2)
information retrieval
(2)
few-shot learning
(2)
Papers
Concept-RuleNet: Grounded Multi-Agent Neurosymbolic Reasoning in Vision Language Models
AAAI 2026
Retrieving Counterfactuals Improves Visual In-Context Learning
CVPR 2026
SAGE: Spuriousness-Aware Guided Prompt Exploration for Mitigating Multimodal Bias
AAAI 2026
SlideBot: A Multi-Agent Framework for Generating Informative, Reliable, Multi-Modal Presentations
AAAI 2026
ASCENT-ViT: Attention-based Scale-aware Concept Learning Framework for Enhanced Alignment in Vision Transformers
IJCAI 2025
COCO-Tree: Compositional Hierarchical Concept Trees for Enhanced Reasoning in Vision-Language Models
EMNLP 2025
GCAV: A Global Concept Activation Vector Framework for Cross-Layer Consistency in Interpretability
ICCV 2025
InfAL: Inference Time Adversarial Learning for Improving Research Ideation
EMNLP 2025
MedCite: Can Language Models Generate Verifiable Text for Medicine?
ACL 2025
NeuronTune: Towards Self-Guided Spurious Bias Mitigation
ICML 2025
ShortcutProbe: Probing Prediction Shortcuts for Learning Robust Models
IJCAI 2025
Toward Reliable Scientific Hypothesis Generation: Evaluating Truthfulness and Hallucination in Large Language Models
IJCAI 2025
AdvST: Revisiting Data Augmentations for Single Domain Generalization
AAAI 2024
A Self-explaining Neural Architecture for Generalizable Concept Learning
IJCAI 2024
Benchmarking Retrieval-Augmented Generation for Medicine
ACL 2024
Benchmarking Spurious Bias in Few-Shot Image Classifiers
ECCV 2024
FedMBridge: Bridgeable Multimodal Federated Learning
ICML 2024
Generalizing to Unseen Domains via Text-guided Augmentation
ECCV 2024
Learning Robust Classifiers with Self-Guided Spurious Correlation Mitigation
IJCAI 2024
MedCalc-Bench: Evaluating Large Language Models for Medical Calculations
NeurIPS 2024
On Disentanglement of Asymmetrical Knowledge Transfer for Modality-Task Agnostic Federated Learning
AAAI 2024
On the Role of Server Momentum in Federated Learning
AAAI 2024
Federated Conditional Stochastic Optimization
NeurIPS 2023
On Task-personalized Multimodal Few-shot Learning for Visually-rich Document Entity Retrieval
EMNLP 2023
Solving a Class of Non-Convex Minimax Optimization in Federated Learning
NeurIPS 2023
Understanding and Enhancing Robustness of Concept-Based Models
AAAI 2023
CLEAR: Generative Counterfactual Explanations on Graphs
NeurIPS 2022
Towards Automating Model Explanations with Certified Robustness Guarantees
AAAI 2022
Multi-Cause Effect Estimation with Disentangled Confounder Representation
IJCAI 2021
EC-GAN: Inferring Brain Effective Connectivity via Generative Adversarial Networks
AAAI 2020
Pairwise Learning with Differential Privacy Guarantees
AAAI 2020
Towards Interpretation of Pairwise Learning
AAAI 2020
AffinityNet: Semi-Supervised Few-Shot Learning for Disease Type Prediction
AAAI 2019
Deep Metric Learning: The Generalization Analysis and an Adaptive Algorithm
IJCAI 2019
Metric Learning on Healthcare Data with Incomplete Modalities
IJCAI 2019
On the Estimation of Treatment Effect with Text Covariates
IJCAI 2019
Privacy-aware Synthesizing for Crowdsourced Data
IJCAI 2019
Representation Learning for Treatment Effect Estimation from Observational Data
NeurIPS 2018
A Correlated Topic Model Using Word Embeddings
IJCAI 2017