31 citations · 125 across the 24 of their papers we have counts for
24 papers
MPL: Multiple Programming Languages with Large Language Models for Information Extraction
Bo Li, Gexiang Fang, Wei Ye +4
Recent research in information extraction (IE) focuses on utilizing code-style inputs to enhance structured output generation. The intuition behind this is that the programming lan…
C^2M-DoT: Cross-modal consistent multi-view medical report generation with domain transfer network
Ruizhi Wang, Xiangtao Wang, Jie Zhou +2
In clinical scenarios, multiple medical images with different views are usually generated simultaneously, and these images have high semantic consistency. However, most existing me…
AMLP: Adjustable Masking Lesion Patches for Self-Supervised Medical Image Segmentation
Xiangtao Wang, Ruizhi Wang, Thomas Lukasiewicz +1
Self-supervised masked image modeling (MIM) methods have shown promising performances on analyzing natural images. However, directly applying such methods to medical image segmenta…
MvCo-DoT:Multi-View Contrastive Domain Transfer Network for Medical Report Generation
Ruizhi Wang, Xiangtao Wang, Zhenghua Xu +3
In clinical scenarios, multiple medical images with different views are usually generated at the same time, and they have high semantic consistency. However, the existing medical r…
MPS-AMS: Masked Patches Selection and Adaptive Masking Strategy Based Self-Supervised Medical Image Segmentation
Xiangtao Wang, Ruizhi Wang, Biao Tian +5
Existing self-supervised learning methods based on contrastive learning and masked image modeling have demonstrated impressive performances. However, current masked image modeling…
Multi-Head Feature Pyramid Networks for Breast Mass Detection
Hexiang Zhang, Zhenghua Xu, Dan Yao +3
Analysis of X-ray images is one of the main tools to diagnose breast cancer. The ability to quickly and accurately detect the location of masses from the huge amount of image data…
Hybrid Reinforced Medical Report Generation with M-Linear Attention and Repetition Penalty
Wenting Xu, Zhenghua Xu, Junyang Chen +2
To reduce doctors' workload, deep-learning-based automatic medical report generation has recently attracted more and more research efforts, where deep convolutional neural networks…
PCA: Semi-supervised Segmentation with Patch Confidence Adversarial Training
Zihang Xu, Zhenghua Xu, Shuo Zhang +1
Deep learning based semi-supervised learning (SSL) methods have achieved strong performance in medical image segmentation, which can alleviate doctors' expensive annotation by util…
Associative Memories via Predictive Coding
Tommaso Salvatori, Yuhang Song, Yujian Hong +5
Associative memories in the brain receive and store patterns of activity registered by the sensory neurons, and are able to retrieve them when necessary. Due to their importance in…
RSG: A Simple but Effective Module for Learning Imbalanced Datasets
Jianfeng Wang, Thomas Lukasiewicz, Xiaolin Hu +2
Imbalanced datasets widely exist in practice and area great challenge for training deep neural models with agood generalization on infrequent classes. In this work, wepropose a new…
Predictive Coding Can Do Exact Backpropagation on Convolutional and Recurrent Neural Networks
Tommaso Salvatori, Yuhang Song, Thomas Lukasiewicz +2
Predictive coding networks (PCNs) are an influential model for information processing in the brain. They have appealing theoretical interpretations and offer a single mechanism tha…
Reverse Differentiation via Predictive Coding
Tommaso Salvatori, Yuhang Song, Thomas Lukasiewicz +2
Deep learning has redefined the field of artificial intelligence (AI) thanks to the rise of artificial neural networks, which are architectures inspired by their neurological count…
FPAENet: Pneumonia Detection Network Based on Feature Pyramid Attention Enhancement
Xudong Zhang, Bo Wang, Di Yuan +2
Automatic pneumonia Detection based on deep learning has increasing clinical value. Although the existing Feature Pyramid Network (FPN) and its variants have already achieved some…
Reinforced Medical Report Generation with X-Linear Attention and Repetition Penalty
Wenting Xu, Chang Qi, Zhenghua Xu +1
To reduce doctors' workload, deep-learning-based automatic medical report generation has recently attracted more and more research efforts, where attention mechanisms and reinforce…
w-Net: Dual Supervised Medical Image Segmentation Model with Multi-Dimensional Attention and Cascade Multi-Scale Convolution
Bo Wang, Lei Wang, Junyang Chen +3
Deep learning-based medical image segmentation technology aims at automatic recognizing and annotating objects on the medical image. Non-local attention and feature learning by mul…
Efficient Medical Image Segmentation with Intermediate Supervision Mechanism
Di Yuan, Junyang Chen, Zhenghua Xu +3
Because the expansion path of U-Net may ignore the characteristics of small targets, intermediate supervision mechanism is proposed. The original mask is also entered into the netw…
SAG-GAN: Semi-Supervised Attention-Guided GANs for Data Augmentation on Medical Images
Chang Qi, Junyang Chen, Guizhi Xu +3
Recently deep learning methods, in particular, convolutional neural networks (CNNs), have led to a massive breakthrough in the range of computer vision. Also, the large-scale annot…
Detecting Beneficial Feature Interactions for Recommender Systems
Yixin Su, Rui Zhang, Sarah Erfani +1
Feature interactions are essential for achieving high accuracy in recommender systems. Many studies take into account the interaction between every pair of features. However, this…
Segmentation is All You Need
Zehua Cheng, Yuxiang Wu, Zhenghua Xu +2
Region proposal mechanisms are essential for existing deep learning approaches to object detection in images. Although they can generally achieve a good detection performance under…
Arena: A General Evaluation Platform and Building Toolkit for Multi-Agent Intelligence
Yuhang Song, Andrzej Wojcicki, Thomas Lukasiewicz +6
Learning agents that are not only capable of taking tests, but also innovating is becoming a hot topic in AI. One of the most promising paths towards this vision is multi-agent lea…
Mega-Reward: Achieving Human-Level Play without Extrinsic Rewards
Yuhang Song, Jianyi Wang, Thomas Lukasiewicz +4
Intrinsic rewards were introduced to simulate how human intelligence works; they are usually evaluated by intrinsically-motivated play, i.e., playing games without extrinsic reward…
Bandwidth Reduction using Importance Weighted Pruning on Ring AllReduce
Zehua Cheng, Zhenghua Xu
It is inevitable to train large deep learning models on a large-scale cluster equipped with accelerators system. Deep gradient compression would highly increase the bandwidth utili…
Diversity-Driven Extensible Hierarchical Reinforcement Learning
Yuhang Song, Jianyi Wang, Thomas Lukasiewicz +2
Hierarchical reinforcement learning (HRL) has recently shown promising advances on speeding up learning, improving the exploration, and discovering intertask transferable skills. M…
Hybrid Deep-Semantic Matrix Factorization for Tag-Aware Personalized Recommendation
Zhenghua Xu, Cheng Chen, Thomas Lukasiewicz +1
Matrix factorization has now become a dominant solution for personalized recommendation on the Social Web. To alleviate the cold start problem, previous approaches have incorporate…