AViTS models spatial importance via latent-text attention and temporal importance via token-level feature variation across diffusion timesteps, and fuses them to enable spatiotemporal importance-aware selective upsampling: it prioritizes resolution refinement for critical tokens while deferring less important ones, the...
Hao-Ran Qin, Zhen Yan, Shikang Zheng et al.· 0 citations
A statistical observation that the residuals between the features of full computation steps using caching methods and reference full-compute trajectory locally exhibit a zero-mean Gaussian distribution is presented, and a plug-and-play GP-Refiner correction framework is proposed.
Zhi-Rong Shen, Rui-Xin Huang, Chang Zou et al.· 0 citations
This work proposes a general memory compression framework adaptable to various agent memory systems, MemForest, and introduces an anchor-guided propagation retrieval mechanism that retrieves relevant memory nodes from the temporal neighborhoods of key nodes, improving retrieval accuracy.
LinCa decomposes cached features into sub-components with distinct continuity properties via a lightweight invertible network and applies differentiated prediction orders matched to each component, forming a unified Decompose-Predict-Reconstruct pipeline.
Jin-Shan Liu, Hao-Ran Qin, Xiao-Bing Tu et al.· 0 citations
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