Search Results for author: Xiangmin Xu

Found 27 papers, 15 papers with code

Modeling Compositionality with Dependency Graph for Dialogue Generation

no code implementations NAACL (SUKI) 2022 Xiaofeng Chen, YiRong Chen, Xiaofen Xing, Xiangmin Xu, Wenjing Han, Qianfeng Tie

Because of the compositionality of natural language, syntactic structure which contains the information about the relationship between words is a key factor for semantic understanding.

Dialogue Generation

SoulChat: Improving LLMs' Empathy, Listening, and Comfort Abilities through Fine-tuning with Multi-turn Empathy Conversations

1 code implementation1 Nov 2023 YiRong Chen, Xiaofen Xing, Jingkai Lin, huimin zheng, Zhenyu Wang, Qi Liu, Xiangmin Xu

Large language models (LLMs) have been widely applied in various fields due to their excellent capability for memorizing knowledge and chain of thought (CoT).

BianQue: Balancing the Questioning and Suggestion Ability of Health LLMs with Multi-turn Health Conversations Polished by ChatGPT

1 code implementation24 Oct 2023 YiRong Chen, Zhenyu Wang, Xiaofen Xing, huimin zheng, Zhipei Xu, Kai Fang, Junhong Wang, Sihang Li, Jieling Wu, Qi Liu, Xiangmin Xu

Large language models (LLMs) have performed well in providing general and extensive health suggestions in single-turn conversations, exemplified by systems such as ChatGPT, ChatGLM, ChatDoctor, DoctorGLM, and etc.

Robust Depth Linear Error Decomposition with Double Total Variation and Nuclear Norm for Dynamic MRI Reconstruction

no code implementations23 Oct 2023 Junpeng Tan, Chunmei Qing, Xiangmin Xu

By adding linear image domain error analysis, the noise is reduced after under-sampled and DFT processing, and the anti-interference ability of the algorithm is enhanced.

MRI Reconstruction

CorrTalk: Correlation Between Hierarchical Speech and Facial Activity Variances for 3D Animation

no code implementations17 Oct 2023 Zhaojie Chu, Kailing Guo, Xiaofen Xing, Yilin Lan, Bolun Cai, Xiangmin Xu

In this study, we propose a novel framework, CorrTalk, which effectively establishes the temporal correlation between hierarchical speech features and facial activities of different intensities across distinct regions.

Self-supervised Fetal MRI 3D Reconstruction Based on Radiation Diffusion Generation Model

no code implementations16 Oct 2023 Junpeng Tan, Xin Zhang, Yao Lv, Xiangmin Xu, Gang Li

Finally, the experimental results on real-world fetal brain MRI stacks demonstrate the state-of-the-art performance of our method.

3D Reconstruction Super-Resolution

Dynamic Shuffle: An Efficient Channel Mixture Method

no code implementations4 Oct 2023 Kaijun Gong, Zhuowen Yin, Yushu Li, Kailing Guo, Xiangmin Xu

To reduce the data-dependent redundancy, we devise a dynamic shuffle module to generate data-dependent permutation matrices for shuffling.

Binarization Image Classification

LAPP: Layer Adaptive Progressive Pruning for Compressing CNNs from Scratch

no code implementations25 Sep 2023 Pucheng Zhai, Kailing Guo, Fang Liu, Xiaofen Xing, Xiangmin Xu

Therefore the pruning strategy can gradually prune the network and automatically determine the appropriate pruning rates for each layer.

Vesper: A Compact and Effective Pretrained Model for Speech Emotion Recognition

1 code implementation20 Jul 2023 Weidong Chen, Xiaofen Xing, Peihao Chen, Xiangmin Xu

Although PTMs shed new light on artificial general intelligence, they are constructed with general tasks in mind, and thus, their efficacy for specific tasks can be further improved.

Speech Emotion Recognition

DWFormer: Dynamic Window transFormer for Speech Emotion Recognition

1 code implementation3 Mar 2023 Shuaiqi Chen, Xiaofen Xing, Weibin Zhang, Weidong Chen, Xiangmin Xu

Self-attention mechanism is applied within windows for capturing temporal important information locally in a fine-grained way.

Speech Emotion Recognition

Superpoint Transformer for 3D Scene Instance Segmentation

1 code implementation28 Nov 2022 Jiahao Sun, Chunmei Qing, Junpeng Tan, Xiangmin Xu

The key step in this framework is a novel query decoder with transformers that can capture the instance information through the superpoint cross-attention mechanism and generate the superpoint masks of the instances.

3D Instance Segmentation 3D Object Detection +3

Context Sensing Attention Network for Video-based Person Re-identification

no code implementations6 Jul 2022 Kan Wang, Changxing Ding, Jianxin Pang, Xiangmin Xu

In this work, we propose a novel Context Sensing Attention Network (CSA-Net), which improves both the frame feature extraction and temporal aggregation steps.

Video-Based Person Re-Identification

Compact Model Training by Low-Rank Projection with Energy Transfer

1 code implementation12 Apr 2022 Kailing Guo, Zhenquan Lin, Xiaofen Xing, Fang Liu, Xiangmin Xu

In this paper, we devise a new training method, low-rank projection with energy transfer (LRPET), that trains low-rank compressed networks from scratch and achieves competitive performance.

Low-rank compression

Weight Evolution: Improving Deep Neural Networks Training through Evolving Inferior Weight Values

1 code implementation9 Oct 2021 Zhenquan Lin, Kailing Guo, Xiaofen Xing, Xiangmin Xu

Comprehensive experiments show that WE outperforms the other reactivation methods and plug-in training methods with typical convolutional neural networks, especially lightweight networks.

To Deconvolve, or Not to Deconvolve: Inferences of Neuronal Activities using Calcium Imaging Data

no code implementations3 Mar 2021 Tong Shen, Gyorgy Lur, Xiangmin Xu, Zhaoxia Yu

With the increasing popularity of calcium imaging data in neuroscience research, methods for analyzing calcium trace data are critical to address various questions.


Listwise View Ranking for Image Cropping

1 code implementation14 May 2019 Weirui Lu, Xiaofen Xing, Bolun Cai, Xiangmin Xu

However, the performance of ranking-based methods is often poor and this is mainly due to two reasons: 1) image cropping is a listwise ranking task rather than pairwise comparison; 2) the rescaling caused by pooling layer and the deformation in view generation damage the performance of composition learning.

Image Cropping

BIT: Biologically Inspired Tracker

1 code implementation23 Apr 2019 Bolun Cai, Xiangmin Xu, Xiaofen Xing, Kui Jia, Jie Miao, DaCheng Tao

Visual tracking is challenging due to image variations caused by various factors, such as object deformation, scale change, illumination change and occlusion.

Visual Tracking

Geometry Processing of Conventionally Produced Mouse Brain Slice Images

no code implementations27 Dec 2017 Nitin Agarwal, Xiangmin Xu, Gopi Meenakshisundaram

In this paper we present techniques and algorithms for automatic registration and 3D reconstruction of conventionally produced mouse brain slices in a standardized atlas space.

3D Reconstruction

Deep Sampling Networks

no code implementations4 Dec 2017 Bolun Cai, Xiangmin Xu, Kailing Guo, Kui Jia, DaCheng Tao

With the powerful down-sampling process, the co-training DSN set a new state-of-the-art performance for image super-resolution.

Image Compression Image Super-Resolution

FReLU: Flexible Rectified Linear Units for Improving Convolutional Neural Networks

2 code implementations25 Jun 2017 Suo Qiu, Xiangmin Xu, Bolun Cai

Rectified linear unit (ReLU) is a widely used activation function for deep convolutional neural networks.

Image Classification

Manifold Regularized Slow Feature Analysis for Dynamic Texture Recognition

no code implementations9 Jun 2017 Jie Miao, Xiangmin Xu, Xiaofen Xing, DaCheng Tao

However, complex temporal variations require high-level semantic representations to fully achieve temporal slowness, and thus it is impractical to learn a high-level representation from dynamic textures directly by SFA.

Dynamic Texture Recognition Scene Recognition

Single Image Super-Resolution Using Multi-Scale Convolutional Neural Network

no code implementations15 May 2017 Xiaoyi Jia, Xiangmin Xu, Bolun Cai, Kailing Guo

However, the previous methods mainly restore images from one single area in the low resolution (LR) input, which limits the flexibility of models to infer various scales of details for high resolution (HR) output.

Image Super-Resolution

Multi-scale Convolutional Neural Networks for Crowd Counting

1 code implementation8 Feb 2017 Lingke Zeng, Xiangmin Xu, Bolun Cai, Suo Qiu, Tong Zhang

Crowd counting on static images is a challenging problem due to scale variations.

Crowd Counting

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