4 papers
PROMPTMINER: Black-Box Prompt Stealing against Text-to-Image Generative Models via Reinforcement Learning and Fuzz Optimization
Mingzhe Li, Renhao Zhang, Zhiyang Wen +4
Text-to-image (T2I) generative models such as Stable Diffusion and FLUX can synthesize realistic, high-quality images directly from textual prompts. The resulting image quality dep…
Which Rewards Matter? Reward Selection for Reinforcement Learning under Limited Feedback
Shreyas Chaudhari, Renhao Zhang, Philip S. Thomas +1
The ability of reinforcement learning algorithms to learn effective policies is determined by the rewards available during training. However, for practical problems, obtaining larg…
Enriching GNNs with Text Contextual Representations for Detecting Disinformation Campaigns on Social Media
Bruno Croso Cunha da Silva, Thomas Palmeira Ferraz, Roseli De Deus Lopes
Disinformation on social media poses both societal and technical challenges, requiring robust detection systems. While previous studies have integrated textual information into pro…
Abstract Reward Processes: Leveraging State Abstraction for Consistent Off-Policy Evaluation
Shreyas Chaudhari, Ameet Deshpande, Bruno Castro da Silva +1
Evaluating policies using off-policy data is crucial for applying reinforcement learning to real-world problems such as healthcare and autonomous driving. Previous methods for off-…