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20212026
most citedAchieving on-Mobile Real-Time Super-Resolution with Neural Architecture and Pruning Search

4 citations · 12 across the 22 of their papers we have counts for

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10 papers · 1 filter

cs.CV2024

SnapGen-V: Generating a Five-Second Video within Five Seconds on a Mobile Device

Yushu Wu, Zhixing Zhang, Yanyu Li +11

We have witnessed the unprecedented success of diffusion-based video generation over the past year. Recently proposed models from the community have wielded the power to generate c…

cs.CV2024

Fast and Memory-Efficient Video Diffusion Using Streamlined Inference

Zheng Zhan, Yushu Wu, Yifan Gong +7

The rapid progress in artificial intelligence-generated content (AIGC), especially with diffusion models, has significantly advanced development of high-quality video generation. H…

cs.AI2024

Search for Efficient Large Language Models

Xuan Shen, Pu Zhao, Yifan Gong +7

Large Language Models (LLMs) have long held sway in the realms of artificial intelligence research. Numerous efficient techniques, including weight pruning, quantization, and disti…

cs.LG2024

Rethinking Token Reduction for State Space Models

Zheng Zhan, Yushu Wu, Zhenglun Kong +6

Recent advancements in State Space Models (SSMs) have attracted significant interest, particularly in models optimized for parallel training and handling long-range dependencies. A…

cs.CV2024

Lotus: learning-based online thermal and latency variation management for two-stage detectors on edge devices

Yifan Gong, Yushu Wu, Zheng Zhan +5

Two-stage object detectors exhibit high accuracy and precise localization, especially for identifying small objects that are favorable for various edge applications. However, the h…

cs.CV2024

Exploring Token Pruning in Vision State Space Models

Zheng Zhan, Zhenglun Kong, Yifan Gong +8

State Space Models (SSMs) have the advantage of keeping linear computational complexity compared to attention modules in transformers, and have been applied to vision tasks as a ne…

cs.AI2024★ 1 cited

Digital Avatars: Framework Development and Their Evaluation

Timothy Rupprecht, Sung-En Chang, Yushu Wu +9

We present a novel prompting strategy for artificial intelligence driven digital avatars. To better quantify how our prompting strategy affects anthropomorphic features like humor,…

cs.CV2024

AyE-Edge: Automated Deployment Space Search Empowering Accuracy yet Efficient Real-Time Object Detection on the Edge

Chao Wu, Yifan Gong, Liangkai Liu +7

Object detection on the edge (Edge-OD) is in growing demand thanks to its ever-broad application prospects. However, the development of this field is rigorously restricted by the d…

cs.CV2024★ 1 cited

SF-V: Single Forward Video Generation Model

Zhixing Zhang, Yanyu Li, Yushu Wu +9

Diffusion-based video generation models have demonstrated remarkable success in obtaining high-fidelity videos through the iterative denoising process. However, these models requir…

cs.SD2024

"It is okay to be uncommon": Quantizing Sound Event Detection Networks on Hardware Accelerators with Uncommon Sub-Byte Support

Yushu Wu, Xiao Quan, Mohammad Rasool Izadi +1

If our noise-canceling headphones can understand our audio environments, they can then inform us of important sound events, tune equalization based on the types of content we liste…