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Adversarial Learning

4854 directly classified papers

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Papers

DeepDRK: Deep Dependency Regularized Knockoff for Feature Selection NIPS 2024
Adversarially Robust Dense-Sparse Tradeoffs via Heavy-Hitters NIPS 2024
High-dimensional (Group) Adversarial Training in Linear Regression NIPS 2024
Robust and Faster Zeroth-Order Minimax Optimization: Complexity and Applications NIPS 2024
GSGAN: Adversarial Learning for Hierarchical Generation of 3D Gaussian Splats NIPS 2024
Exploring the Precise Dynamics of Single-Layer GAN Models: Leveraging Multi-Feature Discriminators for High-Dimensional Subspace Learning NIPS 2024
GuardT2I: Defending Text-to-Image Models from Adversarial Prompts NIPS 2024
DiffHammer: Rethinking the Robustness of Diffusion-Based Adversarial Purification NIPS 2024
Adversarial Schrödinger Bridge Matching NIPS 2024
When LLM Meets DRL: Advancing Jailbreaking Efficiency via DRL-guided Search NIPS 2024
C-GAIL: Stabilizing Generative Adversarial Imitation Learning with Control Theory NIPS 2024
On Unsupervised Domain Adaptation: Pseudo Label Guided Mixup for Adversarial Prompt Tuning AAAI 2024
Robust Safety Classifier Against Jailbreaking Attacks: Adversarial Prompt Shield NAACL 2024
Masking Latent Gender Knowledge for Debiasing Image Captioning NAACL 2024
Improving Word Sense Induction through Adversarial Forgetting of Morphosyntactic Information NAACL 2024
ReEval: Automatic Hallucination Evaluation for Retrieval-Augmented Large Language Models via Transferable Adversarial Attacks NAACL 2024
SemRoDe: Macro Adversarial Training to Learn Representations that are Robust to Word-Level Attacks NAACL 2024
Pointing Out the Shortcomings of Relation Extraction Models with Semantically Motivated Adversarials COLING 2024
ORTicket: Let One Robust BERT Ticket Transfer across Different Tasks COLING 2024
Opinions Are Not Always Positive: Debiasing Opinion Summarization with Model-Specific and Model-Agnostic Methods COLING 2024
On the Impact of Hard Adversarial Instances on Overfitting in Adversarial Training JMLR 2024
Sample-efficient Adversarial Imitation Learning JMLR 2024
Achieving Fairness through Separability: A Unified Framework for Fair Representation Learning AISTATS 2024
RAMP: Boosting Adversarial Robustness Against Multiple $l_p$ Perturbations for Universal Robustness NIPS 2024
Adversarially Trained Weighted Actor-Critic for Safe Offline Reinforcement Learning NIPS 2024