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20232026
most citedHybrid SD: Edge-Cloud Collaborative Inference for Stable Diffusion Models

4 citations · 5 across the 12 of their papers we have counts for

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cs.CV2026

SelfLift: Accelerating Few-Step Diffusion via Self-Recovering Resolution Transition

Tingyan Wen, Chenqian Yan, Xurui Peng +4

Few-step diffusion models substantially compress temporal computation, making the spatial cost of each model evaluation an increasingly dominant source of inference latency. Progre…

cs.AI2026

Accelerating Unified Multimodal Models with Core-Expansion Routing and Unified Computation Scheduling

Wengyi Zhan, Chenqian Yan, Songwei Liu +2

Unified multimodal models jointly support understanding and generation, but incur substantial redundant computation across tokens, layers, and generation timesteps. Through token-i…

cs.CV2026

Motion-Aware Caching for Efficient Autoregressive Video Generation

Jing Xu, Yuexiao Ma, Xuzhe Zheng +7

Autoregressive video generation paradigms offer theoretical promise for long video synthesis, yet their practical deployment is hindered by the computational burden of sequential i…

cs.CV2026

DreamLite: A Lightweight On-Device Unified Model for Image Generation and Editing

Kailai Feng, Yuxiang Wei, Bo Chen +5

Diffusion models have made significant progress in both text-to-image (T2I) generation and text-guided image editing. However, these models are typically built with billions of par…

cs.LG2026

S2O: Early Stopping for Sparse Attention via Online Permutation

Yu Zhang, Songwei Liu, Chenqian Yan +4

Attention scales quadratically with sequence length, fundamentally limiting long-context inference. Existing block-granularity sparsification can reduce latency, but coarse blocks…