2 citations · 2 across the 4 of their papers we have counts for
5 papers
Position: Preventing AI-Generated CSAM Necessitates New Approaches to AI Safety
Neil Kale, Rebecca Portnoff, Pratiksha Thaker +5
Modern artificial intelligence (AI) systems present profound new risks to child safety. AI is increasingly being misused to create AI-generated child sexual abuse material, facilit…
Evaluation without Generation: Non-Generative Assessment of Harmful Model Specialization with Applications to CSAM
Vinith M. Suriyakumar, Ayush Sekhari, Lena Stempfle +5
Auditing the fine-tunes of open-weight generative models for harmful specialization has become a new governance challenge for model hosting platforms. The standard toolkit, generat…
Misinformation Mitigation under Differential Propagation Rates and Temporal Penalties
Michael Simpson, Farnoosh Hashemi, Laks V. S. Lakshmanan
We propose an information propagation model that captures important temporal aspects that have been well observed in the dynamics of fake news diffusion, in contrast with the diffu…
Reverse Prevention Sampling for Misinformation Mitigation in Social Networks
Michael Simpson, Venkatesh Srinivasan, Alex Thomo
In this work, we consider misinformation propagating through a social network and study the problem of its prevention. In this problem, a "bad" campaign starts propagating from a s…
Clearing Contamination in Large Networks
Michael Simpson, Venkatesh Srinivasan, Alex Thomo
In this work, we study the problem of clearing contamination spreading through a large network where we model the problem as a graph searching game. The problem can be summarized a…