8 papers
TMP: Tree-structured Mixed-policy Pruning for Large-scale Image Generation and Editing
Peizhen Zhang, Yang Li, Xunsong Li +10
Modern image generation model rapidly grows their sizes to meet high-fidelity image synthesis. However, they gradually become unaffordable for their enormous parameter consumption…
On the Sparsity-Storage-Accuracy Tradeoff in Parsimoniously Activated Dictionary Learning
Zihui Zhao, Yuanbo Tang, Yang Li
Dictionary learning has long been studied from both optimization and probabilistic perspectives. While formulations with element-wise sparsity regularization (e.g., L1-based sparse…
CrossFlow: One-Step Generation Across Latent and Pixel Spaces
Xiyuan Wang, Xiao Zhang, Yang Li +4
Most diffusion and flow-matching generators define the prior, probability path, and prediction target in the same representation space. Latent diffusion improves efficiency by movi…
Toward Temporal Realism in City-Scale Crisis Response Simulation using LLM Agents
Anping Zhang, Yang Tan, Yuanbo Tang +4
Human collective participation is rarely steady in time: it is bursty, with short episodes of intense activity separated by long quiet intervals. In crisis response and community m…
Looped World Models
Hongyuan Adam Lu, Z. L. Victor Wei, Qun Zhang +28
Current world models face a fundamental tension: faithful long-horizon simulation demands deep computation, but deeper models are expensive to deploy and prone to compounding error…
PhysFire-WM: A Physics-Informed World Model for Emulating Fire Spread Dynamics
Nan Zhou, Huandong Wang, Jiahao Li +4
Fine-grained fire prediction plays a crucial role in emergency response. Infrared images and fire masks provide complementary thermal and boundary information, yet current methods…
A Unified Probabilistic Framework for Dictionary Learning with Parsimonious Activation
Zihui Zhao, Yuanbo Tang, Jieyu Ren +2
Dictionary learning is traditionally formulated as an -regularized signal reconstruction problem. While recent developments have incorporated discriminative, hierarchical, or…
LFTR: Learning-Free Token Reduction for Multimodal Large Language Models
Zihui Zhao, Yingxin Li, Yang Li
Multimodal Large Language Models (MLLMs) have demonstrated exceptional success in various multimodal tasks, yet their deployment is frequently limited by substantial computational…