3 papers
cs.CR2026
The Orthogonal Vulnerabilities of Generative AI Watermarks: A Comparative Empirical Benchmark of Spatial and Latent Provenance
Jesse Yu, Nicholas Wei
As open-weights generative AI rapidly proliferates, the ability to synthesize hyper-realistic media has introduced profound challenges to digital trust. Automated disinformation an…
cs.LG2024
Accelerated AI Inference via Dynamic Execution Methods
Haim Barad, Jascha Achterberg, Tien Pei Chou +1
In this paper, we focus on Dynamic Execution techniques that optimize the computation flow based on input. This aims to identify simpler problems that can be solved using fewer res…
cs.CV2024
Step Saver: Predicting Minimum Denoising Steps for Diffusion Model Image Generation
Jean Yu, Haim Barad
In this paper, we introduce an innovative NLP model specifically fine-tuned to determine the minimal number of denoising steps required for any given text prompt. This advanced mod…