Xingyu Zhao
19 papers · 2019–2026 · 8 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.
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Machine Learning
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Artificial Intelligence
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Deep Learning
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representation learning
(6)
adversarial robustness
(3)
adversarial training
(2)
spatio-temporal data
(2)
explainable ai
(2)
self-supervised learning
(2)
transfer learning
(2)
contrastive learning
(2)
adversarial perturbation
(2)
bayesian inference
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feature representation
(2)
generative model
(2)
attention mechanism
(1)
risk management
(1)
uncertainty quantification
(1)
image retrieval
(1)
few-shot learning
(1)
image classification
(1)
deepfake detection
(1)
multi-label learning
(1)
Papers
Fragile by Design: On the Limits of Adversarial Defenses in Personalized DreamBooth Generation
AAAI 2026
Self-Supervised Cross-City Trajectory Representation Learning Based on Meta-Learning
AAAI 2026
TrajAgg: Dual-Scale Feature Aggregation with Hybrid Training for Trajectory Similarity Computation in Free Space
AAAI 2026
Adversarial Training for Probabilistic Robustness
ICCV 2025
Correlation-Attention Masked Temporal Transformer for User Identity Linkage Using Heterogeneous Mobility Data
AAAI 2025
Risk Controlled Image Retrieval
AAAI 2025
Scalable Trajectory-User Linking with Dual-Stream Representation Networks
AAAI 2025
SIDA: Social Media Image Deepfake Detection, Localization and Explanation with Large Multimodal Model
CVPR 2025
Position: Building Guardrails for Large Language Models Requires Systematic Design
ICML 2024
ProTIP: Probabilistic Robustness Verification on Text-to-Image Diffusion Models against Stochastic Perturbation
ECCV 2024
Representation-Based Robustness in Goal-Conditioned Reinforcement Learning
AAAI 2024
TARP-VP: Towards Evaluation of Transferred Adversarial Robustness and Privacy on Label Mapping Visual Prompting Models
NeurIPS 2024
Imbalanced Label Distribution Learning
AAAI 2023
Learning to Learn from Corrupted Data for Few-Shot Learning
IJCAI 2023
SAFARI: Versatile and Efficient Evaluations for Robustness of Interpretability
ICCV 2023
Fusion Label Enhancement for Multi-Label Learning
IJCAI 2022
BayLIME: Bayesian local interpretable model-agnostic explanations
UAI 2021
Conditional Self-Supervised Learning for Few-Shot Classification
IJCAI 2021
Probabilistic Model Checking of Robots Deployed in Extreme Environments
AAAI 2019