Xingjun Ma
53 papers · 2017–2026 · 11 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 (73) π Conference Polyglot Β· Gold π Academic Marathon Β· Sprint π Interdisciplinary Bridge Β· Silver π£ Hot Topic Early Bird
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(20)
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Deep Specialist
(22)
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Conference Pioneer
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Prolific Year Β· Prolific
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Century Club Β· Silver
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Renaissance Researcher
(6)
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Venues
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Research topics
Machine Learning
(36)
Artificial Intelligence
(34)
Core AI
(30)
Deep Learning
(29)
Learning Types Β· Machine Learning
(25)
Learning Types Β· Deep Learning
(18)
Application Areas
(14)
Computer Vision
(10)
Optimization & Theory
(10)
Models
(7)
Analysis
(6)
Architectures
(6)
Learning Paradigms
(5)
Processing
(4)
Techniques
(4)
Keywords
adversarial robustness
(7)
adversarial learning
(7)
adversarial example
(7)
backdoor attack
(7)
vision-language model
(6)
neural network
(6)
deep neural network
(6)
adversarial training
(6)
large language model
(5)
adversarial attack
(4)
noisy label
(4)
model compression
(3)
adversarial perturbation
(3)
jailbreak attack
(3)
unlearnable example
(3)
bilevel optimization
(3)
federated learning
(3)
image classification
(2)
loss function
(2)
foundation model
(2)
Papers
Coarse-to-Fine Open-Set Graph Node Classification with Large Language Models
AAAI 2026
Deliberative Searcher: Improving LLM Reliability via Reinforcement Learning with Constraints
ACL 2026
GenBreak: Red Teaming Text-to-Image Generation Using Large Language Models
CVPR 2026
OmniLottie: Generating Vector Animations via Parameterized Lottie Tokens
CVPR 2026
SIDE: Surrogate Conditional Data Extraction from Diffusion Models
AAAI 2026
AIM: Additional Image Guided Generation of Transferable Adversarial Attacks
AAAI 2025
Anyattack: Towards Large-scale Self-supervised Adversarial Attacks on Vision-language Models
CVPR 2025
BlueSuffix: Reinforced Blue Teaming for Vision-Language Models Against Jailbreak Attacks
ICLR 2025
CALM: Curiosity-Driven Auditing for Large Language Models
AAAI 2025
Detecting Backdoor Samples in Contrastive Language Image Pretraining
ICLR 2025
Free-Form Motion Control: Controlling the 6D Poses of Camera and Objects in Video Generation
ICCV 2025
HoneypotNet: Backdoor Attacks Against Model Extraction
AAAI 2025
IDEATOR: Jailbreaking and Benchmarking Large Vision-Language Models Using Themselves
ICCV 2025
Optimizing Cross-Client Domain Coverage for Federated Instruction Tuning of Large Language Models
EMNLP 2025
StolenLoRA: Exploring LoRA Extraction Attacks via Synthetic Data
ICCV 2025
TAPT: Test-Time Adversarial Prompt Tuning for Robust Inference in Vision-Language Models
CVPR 2025
Towards Million-Scale Adversarial Robustness Evaluation With Stronger Individual Attacks
CVPR 2025
X-Transfer Attacks: Towards Super Transferable Adversarial Attacks on CLIP
ICML 2025
Adversarial Prompt Tuning for Vision-Language Models
ECCV 2024
Constrained Intrinsic Motivation for Reinforcement Learning
IJCAI 2024
Fake Alignment: Are LLMs Really Aligned Well?
NAACL 2024
LDReg: Local Dimensionality Regularized Self-Supervised Learning
ICLR 2024
UnSeg: One Universal Unlearnable Example Generator is Enough against All Image Segmentation
NeurIPS 2024
Distilling Cognitive Backdoor Patterns within an Image
ICLR 2023
Reconstructive Neuron Pruning for Backdoor Defense
ICML 2023
Transferable Unlearnable Examples
ICLR 2023
Unlearnable Clusters: Towards Label-Agnostic Unlearnable Examples
CVPR 2023
CalFAT: Calibrated Federated Adversarial Training with Label Skewness
NeurIPS 2022
Few-Shot Backdoor Attacks on Visual Object Tracking
ICLR 2022
Fine-mixing: Mitigating Backdoors in Fine-tuned Language Models
EMNLP 2022
Ξ±-IoU: A Family of Power Intersection over Union Losses for Bounding Box Regression
NeurIPS 2021
Anti-Backdoor Learning: Training Clean Models on Poisoned Data
NeurIPS 2021
Exploring Architectural Ingredients of Adversarially Robust Deep Neural Networks
NeurIPS 2021
Gradient Driven Rewards to Guarantee Fairness in Collaborative Machine Learning
NeurIPS 2021
Improving Adversarial Robustness via Channel-wise Activation Suppressing
ICLR 2021
Neural Attention Distillation: Erasing Backdoor Triggers from Deep Neural Networks
ICLR 2021
Noise Doesn't Lie: Towards Universal Detection of Deep Inpainting
IJCAI 2021
Revisiting Adversarial Robustness Distillation: Robust Soft Labels Make Student Better
ICCV 2021
Unlearnable Examples: Making Personal Data Unexploitable
ICLR 2021
Adversarial Camouflage: Hiding Physical-World Attacks With Natural Styles
CVPR 2020
Clean-Label Backdoor Attacks on Video Recognition Models
CVPR 2020
Improving Adversarial Robustness Requires Revisiting Misclassified Examples
ICLR 2020
Normalized Loss Functions for Deep Learning with Noisy Labels
ICML 2020
Reflection Backdoor: A Natural Backdoor Attack on Deep Neural Networks
ECCV 2020
Short-Term and Long-Term Context Aggregation Network for Video Inpainting
ECCV 2020
Skip Connections Matter: On the Transferability of Adversarial Examples Generated with ResNets
ICLR 2020
Generative Image Inpainting with Submanifold Alignment
IJCAI 2019
On the Convergence and Robustness of Adversarial Training
ICML 2019
Symmetric Cross Entropy for Robust Learning With Noisy Labels
ICCV 2019
Characterizing Adversarial Subspaces Using Local Intrinsic Dimensionality
ICLR 2018
Dimensionality-Driven Learning with Noisy Labels
ICML 2018
Iterative Learning With Open-Set Noisy Labels
CVPR 2018
Adversarial Generation of Real-time Feedback with Neural Networks for Simulation-based Training
IJCAI 2017