research
∙
09/12/2023
BDEC:Brain Deep Embedded Clustering model
An essential premise for neuroscience brain network analysis is the succ...
share
research
∙
08/21/2023
Large Language Model as a User Simulator
The unparalleled performance of closed-sourced ChatGPT has sparked effor...
research
∙
08/17/2023
CMB: A Comprehensive Medical Benchmark in Chinese
Large Language Models (LLMs) provide a possibility to make a great break...
research
∙
07/26/2023
GrammarGPT: Exploring Open-Source LLMs for Native Chinese Grammatical Error Correction with Supervised Fine-Tuning
Grammatical error correction aims to correct ungrammatical sentences aut...
research
∙
07/21/2023
Is ChatGPT Involved in Texts? Measure the Polish Ratio to Detect ChatGPT-Generated Text
The remarkable capabilities of large-scale language models, such as Chat...
research
∙
05/24/2023
HuatuoGPT, towards Taming Language Model to Be a Doctor
In this paper, we present HuatuoGPT, a large language model (LLM) for me...
research
∙
05/24/2023
Advancing Topic Segmentation and Outline Generation in Chinese Texts: The Paragraph-level Topic Representation, Corpus, and Benchmark
Topic segmentation and outline generation strive to divide a document in...
research
∙
05/23/2023
Topic-driven Distant Supervision Framework for Macro-level Discourse Parsing
Discourse parsing, the task of analyzing the internal rhetorical structu...
research
∙
05/15/2023
Uncovering the Potential of ChatGPT for Discourse Analysis in Dialogue: An Empirical Study
Large Language Models (LLMs) like ChatGPT have proven a great shallow un...
research
∙
05/02/2023
Topic Shift Detection in Chinese Dialogues: Corpus and Benchmark
Dialogue topic shift detection is to detect whether an ongoing topic has...
research
∙
04/28/2023
Multi-to-Single Knowledge Distillation for Point Cloud Semantic Segmentation
3D point cloud semantic segmentation is one of the fundamental tasks for...
research
∙
04/22/2023
Knowledge Distillation from 3D to Bird's-Eye-View for LiDAR Semantic Segmentation
LiDAR point cloud segmentation is one of the most fundamental tasks for ...
research
∙
04/20/2023
Phoenix: Democratizing ChatGPT across Languages
This paper presents our efforts to democratize ChatGPT across language. ...
research
∙
03/27/2023
ActiveSelfHAR: Incorporating Self Training into Active Learning to Improve Cross-Subject Human Activity Recognition
Deep learning-based human activity recognition (HAR) methods have shown ...
research
∙
02/28/2023
Read Pointer Meters in complex environments based on a Human-like Alignment and Recognition Algorithm
Recently, developing an automatic reading system for analog measuring in...
research
∙
12/07/2021
Image Compressed Sensing Using Non-local Neural Network
Deep network-based image Compressed Sensing (CS) has attracted much atte...
research
∙
10/28/2021
Residual Relaxation for Multi-view Representation Learning
Multi-view methods learn representations by aligning multiple views of t...
research
∙
01/06/2021
Multi-Stage Residual Hiding for Image-into-Audio Steganography
The widespread application of audio communication technologies has speed...
research
∙
11/16/2020
Hierarchical Complementary Learning for Weakly Supervised Object Localization
Weakly supervised object localization (WSOL) is a challenging problem wh...
research
∙
08/04/2020
Entropy Guided Adversarial Model for Weakly Supervised Object Localization
Weakly Supervised Object Localization is challenging because of the lack...
research
∙
01/06/2020
Improving Entity Linking by Modeling Latent Entity Type Information
Existing state of the art neural entity linking models employ attention-...
research
∙
08/01/2019
Optimized Transmission for Parameter Estimation in Wireless Sensor Networks
A central problem in analog wireless sensor networks is to design the ga...
research
∙
01/21/2019
On Compression of Unsupervised Neural Nets by Pruning Weak Connections
Unsupervised neural nets such as Restricted Boltzmann Machines(RBMs) and...
research
∙
08/17/2018
Convolutional Neural Networks based Intra Prediction for HEVC
Traditional intra prediction methods for HEVC rely on using the nearest ...
research
∙
06/19/2018
Deep neural network based sparse measurement matrix for image compressed sensing
Gaussian random matrix (GRM) has been widely used to generate linear mea...
research
∙
04/13/2018
An efficient deep convolutional laplacian pyramid architecture for CS reconstruction at low sampling ratios
The compressed sensing (CS) has been successfully applied to image compr...
research
∙
08/02/2017
An End-to-End Compression Framework Based on Convolutional Neural Networks
Deep learning, e.g., convolutional neural networks (CNNs), has achieved ...
research
∙
07/22/2017
Single Image Super-Resolution with Dilated Convolution based Multi-Scale Information Learning Inception Module
Traditional works have shown that patches in a natural image tend to red...
research
∙
07/22/2017
Deep Networks for Compressed Image Sensing
The compressed sensing (CS) theory has been successfully applied to imag...
research
∙
04/29/2014
Structural Group Sparse Representation for Image Compressive Sensing Recovery
Compressive Sensing (CS) theory shows that a signal can be decoded from ...
research
∙
04/29/2014
Spatially Directional Predictive Coding for Block-based Compressive Sensing of Natural Images
A novel coding strategy for block-based compressive sens-ing named spati...
research
∙
12/25/2012