Search Results for author: Xiao Liang

Found 37 papers, 6 papers with code

面向垂直领域的阅读理解数据增强方法(Method for reading comprehension data enhancement in vertical field)

no code implementations CCL 2020 Zhengwei Lv, Lei Yang, Zhizhong Shi, Xiao Liang, Tao Lei, Duoxing Liu

阅读理解问答系统是利用语义理解等自然语言处理技术, 根据输入问题, 对非结构化文档数据进行分析, 生成一个答案, 具有很高的研究和应用价值。在垂直领域应用过程中, 阅读理解问答数据标注成本高且用户问题表达复杂多样, 使得阅读理解问答系统准确率低、鲁棒性差。针对这一问题, 本文提出一种面向垂直领域的阅读理解问答数据的增强方法, 该方法基于真实用户问题, 构造阅读理解训练数据, 一方面降低标注成本, 另一方面增加训练数据多样性, 提升模型的准确率和鲁棒性。本文用汽车领域数据对该方法进行实验验证, 其结果表明该方法对垂直领域阅读理解模型的准确率和鲁棒性均能有效提升。

Reading Comprehension

AdaViPro: Region-based Adaptive Visual Prompt for Large-Scale Models Adapting

no code implementations20 Mar 2024 Mengyu Yang, Ye Tian, Lanshan Zhang, Xiao Liang, Xuming Ran, Wendong Wang

Recently, prompt-based methods have emerged as a new alternative `parameter-efficient fine-tuning' paradigm, which only fine-tunes a small number of additional parameters while keeping the original model frozen.

Decision Making

GAN Based Near-Field Channel Estimation for Extremely Large-Scale MIMO Systems

no code implementations27 Feb 2024 Ming Ye, Xiao Liang, Cunhua Pan, Yinfei Xu, Ming Jiang, ChunGuo Li

The mixed line-of-sight (LoS) and non-line-of-sight (NLoS) XL-MIMO near-field channel model is adopted to describe the XL-MIMO near-field channel accurately.

Generative Adversarial Network

Exploring Iterative Refinement with Diffusion Models for Video Grounding

1 code implementation26 Oct 2023 Xiao Liang, Tao Shi, Yaoyuan Liang, Te Tao, Shao-Lun Huang

In this paper, we propose DiffusionVG, a novel framework with diffusion models that formulates video grounding as a conditional generation task, where the target span is generated from Gaussian noise inputs and interatively refined in the reverse diffusion process.

Sentence Video Grounding

SSLCL: An Efficient Model-Agnostic Supervised Contrastive Learning Framework for Emotion Recognition in Conversations

1 code implementation25 Oct 2023 Tao Shi, Xiao Liang, Yaoyuan Liang, Xinyi Tong, Shao-Lun Huang

To address these challenges, we propose an efficient and model-agnostic SCL framework named Supervised Sample-Label Contrastive Learning with Soft-HGR Maximal Correlation (SSLCL), which eliminates the need for a large batch size and can be seamlessly integrated with existing ERC models without introducing any model-specific assumptions.

Contrastive Learning Emotion Recognition

Chunk, Align, Select: A Simple Long-sequence Processing Method for Transformers

no code implementations25 Aug 2023 Jiawen Xie, Pengyu Cheng, Xiao Liang, Yong Dai, Nan Du

Although dominant in natural language processing, transformer-based models remain challenged by the task of long-sequence processing, because the computational cost of self-attention operations in transformers swells quadratically with the input sequence length.

Reading Comprehension Text Summarization

High-Resolution Vision Transformers for Pixel-Level Identification of Structural Components and Damage

no code implementations6 Aug 2023 Kareem Eltouny, Seyedomid Sajedi, Xiao Liang

Visual inspection is predominantly used to evaluate the state of civil structures, but recent developments in unmanned aerial vehicles (UAVs) and artificial intelligence have increased the speed, safety, and reliability of the inspection process.

Computational Efficiency Semantic Segmentation +1

TransFusion: A Practical and Effective Transformer-based Diffusion Model for 3D Human Motion Prediction

no code implementations30 Jul 2023 Sibo Tian, Minghui Zheng, Xiao Liang

Predicting human motion plays a crucial role in ensuring a safe and effective human-robot close collaboration in intelligent remanufacturing systems of the future.

Human motion prediction motion prediction

Zero-shot Medical Image Translation via Frequency-Guided Diffusion Models

1 code implementation5 Apr 2023 Yunxiang Li, Hua-Chieh Shao, Xiao Liang, Liyuan Chen, RuiQi Li, Steve Jiang, Jing Wang, You Zhang

However, for medical image translation, the existing diffusion models are deficient in accurately retaining structural information since the structure details of source domain images are lost during the forward diffusion process and cannot be fully recovered through learned reverse diffusion, while the integrity of anatomical structures is extremely important in medical images.

Anatomy SSIM +2

LayoutDiffuse: Adapting Foundational Diffusion Models for Layout-to-Image Generation

no code implementations16 Feb 2023 Jiaxin Cheng, Xiao Liang, Xingjian Shi, Tong He, Tianjun Xiao, Mu Li

Layout-to-image generation refers to the task of synthesizing photo-realistic images based on semantic layouts.

Layout-to-Image Generation

CyberLoc: Towards Accurate Long-term Visual Localization

no code implementations6 Jan 2023 Liu Liu, Yukai Lin, Xiao Liang, Qichao Xu, Miao Jia, Yangdong Liu, Yuxiang Wen, Wei Luo, Jiangwei Li

Second, a single-image-based localization pipeline (retrieval--matching--PnP) is performed to estimate 6-DoF camera poses for each query image, one for each 3D map.

Autonomous Driving Image-Based Localization +3

Cepstral Coefficients for Earthquake Damage Assessment of Bridges Leveraging Deep Learning

no code implementations21 Oct 2022 Seyedomid Sajedi, Xiao Liang

The developed strategy for spatio-temporal analysis of signals enhances the robustness of damage diagnosis frameworks that utilize deep learning for monitoring lifeline structures.

Deep Learning based Direct Segmentation Assisted by Deformable Image Registration for Cone-Beam CT based Auto-Segmentation for Adaptive Radiotherapy

no code implementations7 Jun 2022 Xiao Liang, Howard Morgan, Ti Bai, Michael Dohopolski, Dan Nguyen, Steve Jiang

We found that DL-based direct segmentation on CBCT trained with pseudo labels and without influencer volumes shows poor performance compared to DIR-based segmentation.

Image Registration Segmentation

Modality-Balanced Embedding for Video Retrieval

no code implementations18 Apr 2022 Xun Wang, Bingqing Ke, Xuanping Li, Fangyu Liu, Mingyu Zhang, Xiao Liang, Qiushi Xiao, Cheng Luo, Yue Yu

This modality imbalanceresults from a) modality gap: the relevance between a query and a video text is much easier to learn as the query is also a piece of text, with the same modality as the video text; b) data bias: most training samples can be solved solely by text matching.

Retrieval Text Matching +1

Segmentation by Test-Time Optimization (TTO) for CBCT-based Adaptive Radiation Therapy

no code implementations8 Feb 2022 Xiao Liang, Jaehee Chun, Howard Morgan, Ti Bai, Dan Nguyen, Justin C. Park, Steve Jiang

Firstly, we trained a population model with 200 patients, and then applied TTO to the remaining 39 test patients by refining the trained population model to obtain 39 individualized models.

Image Registration

Whole Brain Segmentation with Full Volume Neural Network

1 code implementation29 Oct 2021 Yeshu Li, Jonathan Cui, Yilun Sheng, Xiao Liang, Jingdong Wang, Eric I-Chao Chang, Yan Xu

To address these issues, we propose to adopt a full volume framework, which feeds the full volume brain image into the segmentation network and directly outputs the segmentation result for the whole brain volume.

Brain Segmentation Representation Learning +1

Large Scale Image Completion via Co-Modulated Generative Adversarial Networks

1 code implementation ICLR 2021 Shengyu Zhao, Jonathan Cui, Yilun Sheng, Yue Dong, Xiao Liang, Eric I Chang, Yan Xu

To overcome this challenge, we propose a generic new approach that bridges the gap between image-conditional and recent modulated unconditional generative architectures via co-modulation of both conditional and stochastic style representations.

Image Inpainting Image-to-Image Translation +1

Nonlinear Cooperative Control of Double Drone-Bar Transportation System

no code implementations15 Nov 2020 Peng Zhang, Yongchun Fang, Xiao Liang, He Lin, wei he

Due to the limitation of the drone's load capacity, various specific tasks need to be accomplished by multiple drones in collaboration.

Dynamical Systems Systems and Control Systems and Control

RelSen: An Optimization-based Framework for Simultaneously Sensor Reliability Monitoring and Data Cleaning

no code implementations19 Apr 2020 Cheng Feng, Xiao Liang, Daniel Schneegass, PengWei Tian

Therefore, in order to enhance the reliability of sensing applications, apart from the physical phenomena/processes of interest, we believe it is also highly important to monitor the reliability of sensors and clean the sensor data before analysis on them being conducted.

Decision Making

Generalizability issues with deep learning models in medicine and their potential solutions: illustrated with Cone-Beam Computed Tomography (CBCT) to Computed Tomography (CT) image conversion

no code implementations16 Apr 2020 Xiao Liang, Dan Nguyen, Steve Jiang

We trained a model on CBCT images acquired from one vendor's scanners for head and neck cancer patients and applied it to images from another vendor's scanners and for other disease sites.

Computed Tomography (CT) Transfer Learning

Model Uncertainty Quantification for Reliable Deep Vision Structural Health Monitoring

no code implementations10 Apr 2020 Seyed Omid Sajedi, Xiao Liang

This paper proposes Bayesian inference for deep vision SHM models where uncertainty can be quantified using the Monte Carlo dropout sampling.

Bayesian Inference Uncertainty Quantification

A Convolutional Cost-Sensitive Crack Localization Algorithm for Automated and Reliable RC Bridge Inspection

no code implementations23 May 2019 Seyed Omid Sajedi, Xiao Liang

In the last decade, camera-equipped unmanned aerial vehicles (UAVs) have been widely used for visual inspections; however, the task of automatically extracting useful information from raw images is still challenging.

Semantic Segmentation

Generating Synthesized Computed Tomography (CT) from Cone-Beam Computed Tomography (CBCT) using CycleGAN for Adaptive Radiation Therapy

no code implementations31 Oct 2018 Xiao Liang, Liyuan Chen, Dan Nguyen, Zhiguo Zhou, Xuejun Gu, Ming Yang, Jing Wang, Steve Jiang

Dose calculation accuracy using sCT images has been improved over the original CBCT images, with the average Gamma Index passing rate increased from 95. 4% to 97. 4% for 1 mm/1% criteria.

Medical Physics

An Attention-Based Word-Level Interaction Model: Relation Detection for Knowledge Base Question Answering

no code implementations30 Jan 2018 Hongzhi Zhang, Guandong Xu, Xiao Liang, Tinglei Huang, Kun fu

Then, instead of merging the sequence into a single vector with pooling operation, soft alignments between words from the question and the relation are learned.

Knowledge Base Question Answering Relation +2

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