Abstract: Machine learning applications are increasingly reliant on black-box pretrained models. To ensure safe use of these models, techniques such as unlearning, guardrails, and watermarking have been proposed to curb […]
Abstract: Large Language Models (LLMs) are vulnerable to adversarial attacks, which bypass common safeguards put in place to prevent these models from generating harmful output. Notably, these attacks can be […]
Abstract: Robust simulation and precise modeling of physical dynamics are essential for advancing perception, planning, and control in the development of generalist physical agents. In this talk, I will present […]
Abstract: American democracy has been undermined by an “infodemic” of fake news, coupled with the widespread segregation of consumers into ideologically homogenous echo chambers by inscrutable algorithms deployed by rapacious […]
Abstract: Neurosymbolic Program Synthesis (NSP) integrates neural networks and symbolic reasoning to tackle complex tasks requiring both perception and logical reasoning. This talk provides an overview of the NSP framework […]
