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Found 3 papers, 3 papers with code
Beyond Worst-case Attacks: Robust RL with Adaptive Defense via Non-dominated Policies
In light of the burgeoning success of reinforcement learning (RL) in diverse real-world applications, considerable focus has been directed towards ensuring RL policies are robust to adversarial attacks during test time.
Benchmarking the Robustness of Image Watermarks
We present WAVES (Watermark Analysis Via Enhanced Stress-testing), a novel benchmark for assessing watermark robustness, overcoming the limitations of current evaluation methods. WAVES integrates detection and identification tasks, and establishes a standardized evaluation protocol comprised of a diverse range of stress tests.
Equal Long-term Benefit Rate: Adapting Static Fairness Notions to Sequential Decision Making
Moreover, we show that the policy gradient of Long-term Benefit Rate can be analytically reduced to standard policy gradient.
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