3 papers
cs.AR2026
DiSC: Resolution-Scalable Acceleration of Diffusion Models by Exploiting Sparsity and Cached Token Reuse with Hash-based Distribution
Jieon Yoon, Hangyeol Lee, Jaehoon Heo +1
Transformer-based diffusion models offer superior scalability and performance but suffer from high computational overhead due to the iterative nature and quadratic complexity of se…
cs.AR2025
APINT: A Full-Stack Framework for Acceleration of Privacy-Preserving Inference of Transformers based on Garbled Circuits
Hyunjun Cho, Jaeho Jeon, Jaehoon Heo +1
As the importance of Privacy-Preserving Inference of Transformers (PiT) increases, a hybrid protocol that integrates Garbled Circuits (GC) and Homomorphic Encryption (HE) is emergi…
cs.AR2025
EXION: Exploiting Inter- and Intra-Iteration Output Sparsity for Diffusion Models
Jaehoon Heo, Adiwena Putra, Jieon Yoon +4
Over the past few years, diffusion models have emerged as novel AI solutions, generating diverse multi-modal outputs from text prompts. Despite their capabilities, they face challe…