Search Results for author: Ying Nie

Found 9 papers, 6 papers with code

PanGu-$π$: Enhancing Language Model Architectures via Nonlinearity Compensation

no code implementations27 Dec 2023 Yunhe Wang, Hanting Chen, Yehui Tang, Tianyu Guo, Kai Han, Ying Nie, Xutao Wang, Hailin Hu, Zheyuan Bai, Yun Wang, Fangcheng Liu, Zhicheng Liu, Jianyuan Guo, Sinan Zeng, Yinchen Zhang, Qinghua Xu, Qun Liu, Jun Yao, Chao Xu, DaCheng Tao

We then demonstrate that the proposed approach is significantly effective for enhancing the model nonlinearity through carefully designed ablations; thus, we present a new efficient model architecture for establishing modern, namely, PanGu-$\pi$.

Language Modelling

LightCLIP: Learning Multi-Level Interaction for Lightweight Vision-Language Models

no code implementations1 Dec 2023 Ying Nie, wei he, Kai Han, Yehui Tang, Tianyu Guo, Fanyi Du, Yunhe Wang

Moreover, based on the observation that the accuracy of CLIP model does not increase correspondingly as the parameters of text encoder increase, an extra objective of masked language modeling (MLM) is leveraged for maximizing the potential of the shortened text encoder.

Image Classification Language Modelling +3

Redistribution of Weights and Activations for AdderNet Quantization

no code implementations20 Dec 2022 Ying Nie, Kai Han, Haikang Diao, Chuanjian Liu, Enhua Wu, Yunhe Wang

To this end, we first thoroughly analyze the difference on distributions of weights and activations in AdderNet and then propose a new quantization algorithm by redistributing the weights and the activations.

Quantization

Network Amplification With Efficient MACs Allocation

2 code implementations Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops 2022 Chuanjian Liu, Kai Han, An Xiao, Ying Nie, Wei zhang, Yunhe Wang

In particular, the proposed method is used to enlarge models sourced by GhostNet, we achieve state-of-the-art 80. 9% and 84. 3% ImageNet top-1 accuracies under the setting of 600M and 4. 4B MACs, respectively.

Dynamic Resolution Network

3 code implementations NeurIPS 2021 Mingjian Zhu, Kai Han, Enhua Wu, Qiulin Zhang, Ying Nie, Zhenzhong Lan, Yunhe Wang

To this end, we propose a novel dynamic-resolution network (DRNet) in which the input resolution is determined dynamically based on each input sample.

GhostSR: Learning Ghost Features for Efficient Image Super-Resolution

4 code implementations21 Jan 2021 Ying Nie, Kai Han, Zhenhua Liu, Chuanjian Liu, Yunhe Wang

Based on the observation that many features in SISR models are also similar to each other, we propose to use shift operation to generate the redundant features (i. e., ghost features).

Image Super-Resolution

A Benchmark for Multi-UAV Task Assignment of an Extended Team Orienteering Problem

1 code implementation1 Sep 2020 Kun Xiao, Junqi Lu, Ying Nie, Lan Ma, Xiangke Wang, Guohui Wang

A benchmark for multi-UAV task assignment is presented in order to evaluate different algorithms.

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