4 accepted papers
Composing pretrained diffusion models provides a cost-effective mechanism to encode constraints and unlock new generative capabilities. Prior work relies on crafting compositional operators that seek to extend set-theoretic notions such as union and intersection to diffusion models, e.g., using a pr…
Naive application of token-wise temperature scaling alters the maximum a posteriori (MAP) estimate at the sequence level, degrading model performance. This issue is exacerbated in MDMs, which estimate sequence-level likelihoods with high variance under different unmasking orders. In this paper, we a…
Online social media provide a platform for people to discuss current events and exchange opinions with their peers. While interactions are predominantly positive, in recent years, there has been a lot of research to understand the conflicts in social networks and how they are based on different view…
We propose and investigate probabilistic guarantees for the adversarial robustness of classification algorithms. While traditional formal verification approaches for robustness are intractable and sampling-based approaches do not provide formal guarantees, our approach is able to efficiently certify…