122 citations · 265 across the 12 of their papers we have counts for
12 papers
Toward Reproducing Network Research Results Using Large Language Models
Qiao Xiang, Yuling Lin, Mingjun Fang +6
Reproducing research results in the networking community is important for both academia and industry. The current best practice typically resorts to three approaches: (1) looking f…
Dual Aggregation Transformer for Image Super-Resolution
Zheng Chen, Yulun Zhang, Jinjin Gu +3
Transformer has recently gained considerable popularity in low-level vision tasks, including image super-resolution (SR). These networks utilize self-attention along different dime…
SwapMoE: Serving Off-the-shelf MoE-based Large Language Models with Tunable Memory Budget
Rui Kong, Yuanchun Li, Qingtian Feng +5
Mixture of experts (MoE) is a popular technique to improve capacity of Large Language Models (LLMs) with conditionally-activated parallel experts. However, serving MoE models on me…
Hierarchical Integration Diffusion Model for Realistic Image Deblurring
Zheng Chen, Yulun Zhang, Ding Liu +4
Diffusion models (DMs) have recently been introduced in image deblurring and exhibited promising performance, particularly in terms of details reconstruction. However, the diffusio…
Xformer: Hybrid X-Shaped Transformer for Image Denoising
Jiale Zhang, Yulun Zhang, Jinjin Gu +3
In this paper, we present a hybrid X-shaped vision Transformer, named Xformer, which performs notably on image denoising tasks. We explore strengthening the global representation o…
Recursive Generalization Transformer for Image Super-Resolution
Zheng Chen, Yulun Zhang, Jinjin Gu +2
Transformer architectures have exhibited remarkable performance in image super-resolution (SR). Since the quadratic computational complexity of the self-attention (SA) in Transform…
Cross Aggregation Transformer for Image Restoration
Zheng Chen, Yulun Zhang, Jinjin Gu +3
Recently, Transformer architecture has been introduced into image restoration to replace convolution neural network (CNN) with surprising results. Considering the high computationa…
Accurate Image Restoration with Attention Retractable Transformer
Jiale Zhang, Yulun Zhang, Jinjin Gu +3
Recently, Transformer-based image restoration networks have achieved promising improvements over convolutional neural networks due to parameter-independent global interactions. To…
TGAN: Deep Tensor Generative Adversarial Nets for Large Image Generation
Zihan Ding, Xiao-Yang Liu, Miao Yin +1
Deep generative models have been successfully applied to many applications. However, existing works experience limitations when generating large images (the literature usually gene…
Task Allocation in Mobile Crowd Sensing: State of the Art and Future Opportunities
Jiangtao Wang, Leye Wang, Yasha Wang +2
Mobile Crowd Sensing (MCS) is the special case of crowdsourcing, which leverages the smartphones with various embedded sensors and user's mobility to sense diverse phenomenon in a…
An LS-Decomposition Approach for Robust Data Recovery in Wireless Sensor Networks
Xiao-Yang Liu, Xiaodong Wang, Linghe Kong +2
Wireless sensor networks are widely adopted in military, civilian and commercial applications, which fuels an exponential explosion of sensory data. However, a major challenge to d…
Two Design Issues in Cognitive Sub-Small Cell for Sojourners
Xin Jin, Abdelwaheb Marzouki, Djamal Zeghlache +2
In this paper, we propound a solution named Cognitive Sub-Small Cell for Sojourners (CSCS) in allusion to a broadly representative small cell scenario, where users can be categoriz…