Adversarial Learning
5,204 papers
Papers per year
3
1
4
6
3
5
10
6
8
18
87
282
558
628
688
663
703
669
694
168
'10
'15
'20
'25
Papers
SurfGen: Adversarial 3D Shape Synthesis With Explicit Surface Discriminators
ICCV 2021
SurFree: A Fast Surrogate-Free Black-Box Attack
CVPR 2021
Symbolic Music Generation with Transformer-GANs
AAAI 2021
Syntactically Diverse Adversarial Network for Knowledge-Grounded Conversation Generation
EMNLP 2021
Targeted Adversarial Training for Natural Language Understanding
NAACL 2021
Task-Aware Variational Adversarial Active Learning
CVPR 2021
TextFlint: Unified Multilingual Robustness Evaluation Toolkit for Natural Language Processing
ACL 2021
TextGAIL: Generative Adversarial Imitation Learning for Text Generation
AAAI 2021
The best of both worlds: stochastic and adversarial episodic MDPs with unknown transition
NeurIPS 2021
The curious case of adversarially robust models: More data can help, double descend, or hurt generalization
UAI 2021
The impact of domain-specific representations on BERT-based multi-domain spoken language understanding
EACL 2021
The Many Faces of Adversarial Risk
NeurIPS 2021
Themis: A Fair Evaluation Platform for Computer Vision Competitions
IJCAI 2021
The Translucent Patch: A Physical and Universal Attack on Object Detectors
CVPR 2021
TIME: Text and Image Mutual-Translation Adversarial Networks
AAAI 2021
TkML-AP: Adversarial Attacks to Top-k Multi-Label Learning
ICCV 2021
To Beam Or Not To Beam: That is a Question of Cooperation for Language GANs
NeurIPS 2021
To be Robust or to be Fair: Towards Fairness in Adversarial Training
ICML 2021
Token-Aware Virtual Adversarial Training in Natural Language Understanding
AAAI 2021
Topology Distance: A Topology-Based Approach for Evaluating Generative Adversarial Networks
AAAI 2021
Towards a Unified Game-Theoretic View of Adversarial Perturbations and Robustness
NeurIPS 2021
Towards Better Robust Generalization with Shift Consistency Regularization
ICML 2021
Towards Better Understanding of Training Certifiably Robust Models against Adversarial Examples
NeurIPS 2021
Towards Defending against Adversarial Examples via Attack-Invariant Features
ICML 2021
Towards Distraction-Robust Active Visual Tracking
ICML 2021