SEBA: Sample-Efficient Black-Box Attacks on Visual Reinforcement Learning

arXiv:2511.09681 · cs.LG, cs.AI · Submitted 2025-11-12 · Read on arXiv

cs.LG, cs.AI

Submitted: 2025-11-12

Updated: 2026-09-02

Terminology

• Reinforcement Learning — 35× in this paper · explained in 4 episodes
• World Model — 25× in this paper · explained in 7 episodes
• Adversarial Attacks — 9× in this paper · explained in 1 episode
• Deep Reinforcement Learning — 9× in this paper · explained in 2 episodes
• Robustness — 6× in this paper · explained in 5 episodes
• Action Space — 5× in this paper · explained in 1 episode
• Benchmark — 5× in this paper · explained in 2 episodes
• Sample Efficiency — 5× in this paper · explained in 4 episodes
• Ablation — 3× in this paper · explained in 1 episode
• Actor — 3× in this paper · explained in 3 episodes
• Fidelity — 3× in this paper · explained in 2 episodes
• Representation Learning — 3× in this paper · explained in 2 episodes
• Transformer — 3× in this paper · explained in 2 episodes
• Ablation study — 2× in this paper · explained in 1 episode
• Embodied AI — 2× in this paper · explained in 2 episodes
• Adversarial Robustness — 1× in this paper · explained in 3 episodes
• Alignment — 1× in this paper · explained in 1 episode
• Contrastive Learning — 1× in this paper · explained in 5 episodes
• Data Augmentation — 1× in this paper · explained in 7 episodes
• Latent Dynamics — 1× in this paper · explained in 2 episodes
• Latent Representation — 1× in this paper · explained in 2 episodes
• Latent Representations — 1× in this paper · explained in 3 episodes
• Latent Space — 1× in this paper · explained in 7 episodes
• Model Drift — 1× in this paper · explained in 4 episodes
• Nash Equilibrium — 1× in this paper · explained in 2 episodes
• Q-learning — 1× in this paper · explained in 3 episodes
• Reinforcement Learning (RL) — 1× in this paper · explained in 25 episodes
• Sample Complexity — 1× in this paper · explained in 15 episodes
• Steering — 1× in this paper · explained in 2 episodes
• Two-Stage Framework — 1× in this paper · explained in 2 episodes

Sources

• Robust Deep Reinforcement Learning against Adversarial Behavior Manipulation

Related papers

• Polynomial-Augmented Neural Networks (PANNs) with Weak Orthogonality Constraints for Enhanced Function and PDE Approximation
• AIRL-S: Unifying Reinforcement Learning and Search-Based Test-Time Scaling via Adversarial Inverse Reinforcement Learning
• Transformers as Bayesian In-Context Experimenters: Smoothness-Adaptive Efficient ATE Estimation
• Convergence issues in Relational Concept Analysis based on AOC-posets
• Beliefs Beyond Posteriors: Local-Consistency Optimisation for Bayesian Neural Networks
• Understanding Diffusion Models via Ratio-Based Function Approximation with SignReLU Networks